Micro-RNA Biomarkers and Methods of Using Same

ABSTRACT

A procedure and an apparatus are described for identifying individuals at risk of pulmonary tumour and/or for diagnosing a pulmonary tumour using the study of levels of expression of miRNA in the blood or another biological fluid. Also described are a method and a compound for reducing or eliminating a risk of pulmonary tumour by rebalancing the miRNAs that are underexpressed or overexpressed.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of Italian Patent Application Nos.MI2011A000172, MI2011A000173 and MI2011A000174, each filed Feb. 7, 2011and U.S. Provisional Application No. 61/522,328, filed Aug. 11, 2011.The contents of each of these applications are incorporated herein byreference in their entirety.

FIELD OF THE INVENTION

The present invention concerns methods for identifying and using, inpre-diagnostic and/or diagnostic stages, special molecular bio-markersidentifiable in biological samples, such as for example whole blood,serum, plasma, saliva or bronchia condensate collected from anindividual.

In more detail, the invention relates to methods for identifyingindividuals at risk of tumour, in particular pulmonary tumour. Theinvention also concerns methods for determining a presence and/or levelof aggressiveness of a tumour, for example a pulmonary tumour, in anindividual.

The invention also relates to diagnostic kits and apparatus usable forsetting up one or more stages of the methods.

Further, the invention concerns methods and pharmaceutical compounds fortreating an individual in whom presence of a tumour has been diagnosed,for example a pulmonary tumour.

The invention also concerns methods and pharmaceutical compounds fortreating an individual in whom a risk of developing a tumour has beenidentified, for example a pulmonary tumour, for reducing and/oreliminating the risk of developing a tumour.

BACKGROUND OF THE INVENTION

As is known, tumours are one of the main causes of death in the world.In particular, pulmonary tumours are the highest in terms of incidence,as they represent about 12% of all the new cases of cancer, andconstitute the main cause of death by cancer in the world, in both menand women.

In Europe about 400,000 new cases are diagnosed per year (80% men, 20%women). In Italy the epidemiology of pulmonary cancer is similar, withan incidence of 34,000 cases per year of which 7,000 are women and27,000 men.

Sadly the incidence and the mortality are very similar due to the highlylethal nature of pulmonary tumour: world-wide mortality 27,500, of which22,000 mend and 5,500 women. This epidemiological data and the scarcelevel of treatability of the illness underline the importance ofidentifying methods which are able to identify as soon as possible anysubjects who might be at risk of developing pulmonary cancer. Further,it is of great interest to develop procedures which can help in thecorrect diagnosis of tumours, in particular pulmonary tumours present inan individual subject under examination.

Notwithstanding these needs, tumour markers available today are fordiagnostic use, i.e. they identify the patients when the disease hasalready developed such as to be identifiable with imaging methods(spiral CT scan). These markers are however few and not specific andessentially comprise biochemical markers such as the evaluation of theprotein CEA (Carcinoembryonic Antigene) and some cytokeratins such asTPA, TPS and Cyfra 21.1.

Also known is a proteomic test (5-protein profile) on the serum, atpresent proposed by Vermillion Inc. and used to indicate a probability(score from 1 to 10) that ovarian masses might be of a malignant nature.This test is used for women who already present ovarian masses of anon-defined nature.

With specific reference to pulmonary tumours, although in recent yearsimportant improvements have been made in the treatment of oncologicalpatients, there is however a need to develop more effective methodswhich can lead to a faster therapeutic intervention in clinicalmanagement of many types of tumours.

At present the majority of pulmonary tumours are diagnosed at a latestage, when the symptoms are clinically evident and, for example withreference to Non-small-cell lung carcinoma (NSCLC), only a third ofpatients with NSCLC exhibits a surgically-resectable disease, anapproach which remains the most effective treatment for this type oftumour.

Notwithstanding recent progress in treatment of pulmonary cancer afterresection and the use of specific treatments for determined moleculartargets, the rate of healing of non-small-cell lung carcinoma (NSCLC)remains low due to the reappearance thereof in patients that areresistant to drugs or who present metastasis.

The effectiveness of the spiral CT scan in identification of pulmonarycancer in heavy smokers is under evaluation in various randomizedclinical studies in Europe and the United States. Owing to the its highlevel of sensitivity there remain various critical points for its use inmodern clinical practice, such as over-diagnosis of indolent nodules,with a consequently high frequency of non-necessary treatments and theverification of the effective impact on mortality.

In this context, in recent years microRNAs have been identified (hereinbelow also MiRNA) as a new class of circulating bio-markers which bytheir nature seem to be very stable and highly specific tissue (Chen X,Cell Res, 2008). MiRNAs are small non-coding RNA molecules (length 19-25nucleotides) having a regulatory function which are able to modulate theexpression of several target genes involved in various molecularmechanisms, among which those involved in transformation processes.

The development of high-throughput technologies has enabled the study ofoverall expression of the profiles of miRNA in cancer (microRNAome)(Cummins J M et al., Proc Natl Acad Sci USA, 2006), revealing that thereexist hundreds of miRNA whose expression is deregulated in tumours(Croce C M, Visone R, A J P, 2009; WO2009/070653, The Ohio StateUniversity Research Foundation).

Apart from the tissue specificity, miRNA possess a high degree ofstability, ease of detection and association with knownclinical-pathological parameters (Lu Jet al., Nature, 2005).

Tests have also been carried out to determine whether miRNAs are stable,detectable and quantifiable not only in the tissues (both deep-frozenand fixed in formalin or paraffin) but also in the bodily fluids. Theresults of this research have demonstrated that miRNAs are also presentin the blood circulation (whole blood, serum and plasma), where they arefound in stable form protected by endogenous RNAsi. Circulating miRNAsare detectable and quantifiable and the studies which have taken theirlevels in oncological patients' biological fluids under examination havereported that some of them present deregulated levels with respect tohealthy individuals (Heneghan H M et al., Ann Surg, 2010; Mitchell P Set al., Proc Natl Acad Sci USA, 2008; Chen X, Cell Res, 2008).

Recent publications report the profile of miRNAs circulating in theserum and plasma of patients having pulmonary tumour (Hu Z, Clin Oncol,2010; Silva J, Eur Respir J, 2010 Shen J, Lab Invest, 2010).

Notwithstanding the presence of diagnostic imaging systems and thestudies relating to microRNAs, there is still the need to identifyprocedures which are able to identify, with a certain degree ofanticipation, individuals at risk of developing pulmonary cancer andpossibly able to predict the development of the forms of cancer, inparticular pulmonary tumour, that are more aggressive and lethal. Thereis also a need to improve the degree of reliability of diagnostictechniques at present available.

SUMMARY OF THE INVENTION

In this situation, the aim of the present invention is to obviate one ormore of the limitations in the known procedures and products.

Thus it is an aim of the invention to provide procedures for earlydetermination of individuals who present a risk of developing a tumour,in particular a pulmonary tumour.

A further aim of the invention is to make available procedures whichassist in the diagnosis of tumour, in particular pulmonary tumours, inhuman subjects.

A further aim of the invention is to make available procedures which canbe easily set up in laboratories, by analyzing biological samplescollected from an individual.

A further aim of the invention is to provide procedures which enablesatisfactory results to be obtained using samples of blood, serum orplasma.

A further aim of the invention is to define diagnostic kits and/orapparatus usable in the above-cited procedures in order to identifyhuman subjects who are at risk of contracting a tumour and/or forassisting in the diagnosis of tumours present in human subjects.

A further aim of the invention is to provide pharmaceutical compoundsand/or treatments which can be used to treat an individual in whom thepresence of a pulmonary tumour has been diagnosed.

A final aim of the invention is to provide pharmaceutical compoundsand/or treatments for reducing and/or eliminating the risk of developinga pulmonary tumour.

One or more of the set aims are substantially attained by a methodand/or a kit and/or a compound and/or an apparatus in accordance withone or more of the accompanying claims.

Aspects of the invention are described herein below.

A first aspect concerns a procedure for identifying individuals at riskof a pulmonary tumour, the procedure comprising steps of: measuring, inat least a sample of biological fluid previously collected from asubject, a value of the level of expression of a plurality of microRNAmolecules; determining when the measured values of the level ofexpression deviate with respect to a predetermined and respectivecontrol criterion.

The microRNA or miRNA molecules are thus used for identifyingindividuals at risk or in a stage in which the tumour has not yetmanifested.

In a second aspect in accordance with the first aspect the step ofdetermining comprises determining the level of expression of at leastsix miRNA from the miRNA listed in Tables Ia, Ic, Ha or He in abiological sample from a subject, and comparing the level of expressionof said miRNA from said sample from said subject to the level ofexpression of said miRNA from a control biological sample. For exampledetermining may comprise determining—in a biological sample from asubject—the level of expression of the six miRNA listed in Table Ib orId or the level of expression of the six miRNA listed in Table IIb orIId, and comparing the level of expression of said six miRNA from saidsample from said subject to the level of expression of said miRNA from acontrol biological sample, wherein a change or deviation in the level ofexpression of said at least six miRNA in said biological sample fromsaid control biological sample identifies a subject at risk ofmanifesting a tumor (Table 1b or Id miRNA are used) or an aggressivetumor (Table IIb or lid miRNA are used).

In a third aspect in accordance with the first aspect the step ofdetermining comprises substeps of calculating a plurality of ratios orreal differences determined by performing the ratio or respectively thedifference between the measured values of the levels of expression of apredetermined number of pairs of the microRNA molecules, comparing eachof the real ratios or differences with a respective control value,determining the real ratios or differences which deviate from therespective ratio value or control difference.

In a fourth aspect in accordance with the third aspect, a step is alsoincluded of determining a number or percentage of real ratios ordifferences which deviate from the respective control value and definingas an individual at risk an individual for whom at least a predeterminednumber or a predetermined percentage of the real ratios or differencesdeviates with respect to the respective ratio value or controldifference.

In a fifth aspect, in accordance with any one of the preceding aspects,for each of the calculated ratios, a respective control ratio isassociated represented by the ratio of the expression values for themicroRNAs in a control sample relating to a biological fluid of the sametype. The control ratio is in reality either a known value, or adetermined value as a mean of measured values in a sufficiently largepopulation of individuals, or a value relating to a fluid samplecollected from a healthy individual.

In a sixth aspect, in accordance with any one of the preceding aspects,the procedure comprises the step of correlating the deviation of apredetermined number or a predetermined percentage of expression levels(i.e. real ratios or differences) with respect to the correspondingcontrol criteria in the presence or absence of risk that the individualclinically presents a pulmonary tumour in a predetermined time.

In a seventh aspect according to the preceding aspect the predeterminedtime is comprised between one and three years, more optionally iscomprised between 12 and 28 months. In other words the method of theinvention is able to significantly anticipate the determination of therisk of contracting a tumour with respect to traditional techniques(such as spiral CT) which have to wait for the disease to manifest atthe level of lacerations or nodules of various mm.

In an eighth aspect in accordance with any one of the preceding aspectsthe procedure comprises a step of correlating the deviation of apredetermined number or a predetermined percentage of expression levelwith respect to the corresponding control criteria to the presence orabsence of risk which the individual manifests clinically an aggressivepulmonary tumour in a predetermined time.

In a ninth aspect, according to the preceding aspect, the predeterminedtime is comprised between one and three years, more optionally between12 and 28 months. In other words the method of the invention is able tosignificantly anticipate the determination of the risk of contracting anaggressive tumour with respect to the traditional techniques (such asspiral CT) which have to wait for the disease to manifest at the levelof lacerations or nodules or various mm.

In a tenth aspect, in accordance with any one of the preceding aspects,calculating the plurality of real ratios or differences comprises usingthe expression values of a predetermined number or a predeterminedpercentage of the miRNAs of Table Ia, Ic, IIa and/or of Table IIc,optionally using the expression values of the miRNAs of Table Ib, Id,IIb and/or of Table IId.

In an eleventh aspect in accordance with any one of aspects 6^(th),7^(th) or 10^(th), calculating the plurality of real ratios ordifferences comprises using the expression values of a predeterminednumber or a predetermined percentage of the miRNAs of Table Ia or Ic.

In a twelfth aspect, according to any one of aspects 8^(th), 9^(th) or10^(th), calculating the plurality of real ratios or differencescomprises using the expression values of a predetermined number or apredetermined percentage of the miRNA of Table IIa or IIc.

In a thirteenth aspect according to any one of the preceding aspects,calculating the plurality of real ratios comprises determining apredetermined number or a predetermined percentage of ratios among thevalues of the expression levels, the ratios being selected from thegroup comprising ratios between values of expression levels of pairs ofmicroRNA as in Table IIIa or IIIc, optionally in which at least 20% aredetermined, more optionally at least 50% and still more optionally allthe ratios of Table IIIa or IIIc.

In a fourteenth aspect in accordance with the preceding claim,determining a predetermined number or a predetermined percentage ofratios comprises calculating at least 20% of the real ratios of TableIIIa or IIIc and in which it comprises a step of defining as anindividual at risk of pulmonary tumour, optionally in a period comprisedbetween one and three years from a collection of the sample ofbiological fluid, an individual for whom at least 30%, optionally atleast 50% of the real ratios calculated deviates with respect to therespective control ratio value.

In a fifteenth aspect in accordance with any one of aspects 13 or 14, inwhich the ratios are those of Table IIIb or IIId.

In a sixteenth aspect in accordance with any one of the precedingaspects, calculating the plurality of real ratios comprises determininga predetermined number or a predetermined percentage of ratios among thevalues of the expression levels, the ratios being selected from thegroup comprising ratios between values of expression levels of pairs ofmicroRNAs as in Table IVa or IVc, optionally in which at least 30% aredetermined, more optionally at least 50%, and still more optionally allthe ratios of Table IVa or IVc.

In a seventeenth aspect according to the preceding aspect, determining apredetermined number or a predetermined percentage of ratios comprisescalculating at least 30% of the real ratios as in Table IVa or IVc, andwherein the procedure comprises a step of defining as an individual atrisk of aggressive pulmonary tumour, optionally in a period comprisedbetween one and three years from collecting a sample of biologicalfluid, an individual for whom at least 50%, optionally at least 75% ofthe real ratios calculated deviates with respect to the respectivecontrol ratio value.

In an eighteenth aspect according to any one of aspects 16 or 17, theratios are those of Table IVb or IVd.

In a nineteenth aspect of any one of the preceding aspects, the steps ofthe procedure are conducted in vitro.

In a twentieth aspect in accordance with any one of the precedingaspects, the biological fluid is one selected from a group comprising:whole blood, a fraction of blood, plasma, serum.

In a twenty-first aspect in accordance with any one of the precedingaspects the pulmonary tumour is one selected from the group comprising:small-cell lung cancer (SCLC), non small-cell lung cancer (NSCLC),pulmonary adenocarcinoma (ADC), bronchio-alveolar carcinoma (BAC),squamous-cell lung carcinoma (SCC), large-cell carcinoma (LC).

In a twenty-second aspect according to any one of the preceding aspects,the sample of biological fluid originates from a smoker individual who,at the moment of the collection of the sample, does not present apulmonary tumour if subjected to imaging diagnostic methods, inparticular the smoker individual not presenting nodules of dimensions ofgreater than 5 mm if subjected to a spiral CT scan.

A twenty-third aspect concerns a medical kit for determiningbiomolecular markers present in a sample of human biological fluid, thekit comprising a platform having a plurality of sites, each of which isdestined to receive a respective discrete quantity of the sample ofbiological fluid, each of the sites comprising a reagent capable ofbonding with at least a respective microRNA of Table Ia, Ic, IIa and/orTable IIc, optionally wherein each of the sites comprises a reagentcapable of bonding with at least a respective microRNA of Table Ib, Id,IIb and/or Table IId.

In a twenty-fourth aspect in accordance with the preceding aspect, thereagent includes at least a reagent selected from among the groupcomprising: a polynucleotide comprising a nucleotide sequence of atleast one of the microRNAs as in Table Ia, Ic, Ha and/or Table IIc,optionally as in Table Ib, Id, IIb and/or Table IId; a polynucleotidecomprising a nucleotide sequence which is complementary to a sequence ofat least one of the microRNAs as in Table Ia, Ic, IIa and/or Table IIc,optionally as in Table Ib, Id, IIb and/or Table IId; a molecular probeconfigured such as to recognize a sequence of at least one of themicroRNAs as in Table Ia, Ic, IIa and/or Table IIc, optionally as inTable Ib, Id, IIb and/or Table IId.

A twenty-fifth aspect concerns a medical apparatus comprising: a unitdefining a seating for receiving one or more of the kits of aspects23^(rd) or 24^(th); means for determining a value of the level ofexpression of the microRNAs as in Table Ia, Ic, IIa and/or Table IIc;means for calculating the values of the real ratios from among thevalues of levels of expression of pairs of microRNAs, the ratios beingselected from those in Table IIa, IIc, IVa and/or Table IVd, optionallythose ratios of Table Ib, IId, IVb and/or those of Table IVd.

In a twenty-sixth aspect according to the preceding aspect, the meansfor determining the value of the expression level comprise one of thetechniques selected from the group: Quantitative Real-time PCR,Microfluidic cards, Microarrays, RT-PCR, quantitative orsemi-quantitative, Northern blot, Solution Hybridization, or Sequencing.

A twenty-eighth aspect comprises an in vitro procedure for identifyingindividuals at risk of tumour and/or for determining a presence ofand/or an aggressiveness of a tumour in an individual, the processcomprising steps of: measuring, in at least a sample of biological fluidpreviously collected from a subject, a value of a level of expression ofa plurality of microRNA molecules; calculating a plurality of realratios determined by calculating a ratio between the measured values ofthe levels of expression of a predetermined number of pairs of themicroRNA molecules; comparing each of the real ratios with a respectivecontrol value.

In a twenty-ninth aspect in accordance with the twenty-eighth aspect,the process comprises determining a number or percentage of real ratioswhich deviate from the respective control value, defining, as anindividual presenting a form of tumour, an individual for whom at leasta predetermined number or a predetermined percentage of the real ratiosdeviates with respect to the respective control ratio value.

In a thirtieth aspect in accordance with the twenty-ninth, a respectivecontrol ratio is associated to each of the calculated ratios,represented by a ratio of the values of expression for the microRNAs ina control sample relative to a biological fluid of a same type.

In a thirty-first aspect, in accordance with the thirtieth or thetwenty-ninth, calculating the plurality of real ratios comprises usingthe values of expression of a predetermined number of the miRNAs as inTable Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc, VIa and/or TableVIc.

In a thirty-second aspect in accordance with any one of aspects from the29^(th) to 31^(st), calculating the plurality of real ratios comprisesdetermining a predetermined number or a predetermined percentage ofratios from among the values of the levels of expression, the ratiosbeing selected from among the group comprising ratios as in Table IIIa,IIIc, IVa, and/or Table IVc and/or in Table VIIa, VIIc, VIIIa and/or inTable VIIIc.

In a thirty-third aspect in accordance with the thirty-second,determining a predetermined number or a predetermined percentage ofratios comprises calculating at least 20% of the real ratios of TableVIIa or VIIc and comprises a step of defining as an individualpresenting a pulmonary tumour an individual for whom at least 30% of thepredetermined number of real ratios as in Table VIIa or VIIc which havebeen calculated deviate with respect to the control value.

In a thirty-fourth aspect in accordance with the thirty-third or thethirty-second, determining a predetermined number or a predeterminedpercentage of ratios comprises calculating at least 20% of the realratios of Table VIIIa or VIIIc and comprises a step of defining as anindividual presenting an aggressive pulmonary tumour an individual inwhom 50%, optionally at least 60%, of the real ratios which have beencalculated deviate with respect to the respective control value.

In a thirty-fifth aspect, in accordance with the thirty-fourth or thethirty-third or the thirty-second, determining the predetermined numberor a predetermined percentage of ratios comprises calculating at least20% of the real ratios of Table IIa or IIc and comprises a step ofdefining as an individual at risk of a pulmonary tumour, optionally in aperiod comprised between one and three years from a collection of thesample of biological fluid, an individual for whom at least 30%,optionally at least 50%, of the real ratios calculated deviate withrespect to the respective control ratio value.

In a thirty-sixth aspect in accordance with the thirty-fifth, thethirty-fourth or the thirty-third or the thirty-second, determining thepredetermined number or a predetermined percentage of ratios comprisescalculating at least 30% of the real ratios of Table IVa or IVc andcomprises a step of defining as an individual at risk of an aggressivepulmonary tumour, optionally in a period comprised between one and threeyears from a collection of the sample of biological fluid, an individualfor whom at least 50%, optionally at least 75%, of the real ratioscalculated deviate with respect to the respective control ratio value.

In a thirty-seventh aspect in accordance with the any one of the aspectsfrom the 28^(th) to the 32^(nd), determining a predetermined number or apredetermined percentage of ratios comprises calculating the real ratiosof Table VIIb or VIId and wherein the procedure comprises a step ofdefining as an individual presenting a pulmonary tumor an individual forwhom at least 80% of the real ratios as in Table VIIb or VIId which havebeen calculated deviate with respect to the control value.

In a thirty-eighth aspect in accordance with the any one of the aspectsfrom the 28^(th) to the 32^(nd), determining a predetermined number or apredetermined percentage of ratios comprises calculating the real ratiosof Table VIIIb or VIIId and wherein the procedure comprises a step ofdefining as an individual presenting an aggressive pulmonary tumor anindividual for whom at least 80% of the real ratios as in Table VIIIb orVIIId which have been calculated deviate with respect to the controlvalue.

In a thirty-ninth aspect in accordance with the any one of the aspectsfrom the 28^(th) to the 32^(nd), determining a predetermined number or apredetermined percentage of ratios comprises calculating the real ratiosof Table IIIb or IIId and wherein the procedure comprises a step ofdefining as individual at risk of a pulmonary tumour, optionally in aperiod comprised between one and three years from a collection of thesample of biological fluid, an individual for whom at least 80% of thereal ratios as in Table IIIb or IIId which have been calculated deviatewith respect to the control value.

In a fortieth aspect in accordance with the any one of the aspects fromthe 28^(th) to the 32^(nd), determining a predetermined number or apredetermined percentage of ratios comprises calculating the real ratiosof Table IVb or IVd and wherein the procedure comprises a step ofdefining as individual at risk of an aggressive pulmonary tumour,optionally in a period comprised between one and three years from acollection of the sample of biological fluid, an individual for whom atleast 80% of the real ratios as in Table IVb or IVd which have beencalculated deviate with respect to the control value.

In a forty-first aspect in accordance with any one of the precedingaspects from the 28^(th) to 40^(th), the biological fluid is oneselected from among a group comprising: whole blood, a fraction ofblood, plasma, serum; saliva or bronchial condensate.

In a forty-second aspect in accordance with any one of the precedingaspects from the 28^(th) to 41^(st), the tumour is a pulmonary tumourselected from among a group comprising: small-cell lung cancer (SCLC),non small-cell lung cancer (NSCLC), pulmonary adenocarcinoma (ADC),bronchio-alveolar carcinoma (BAC), squamous-cell lung carcinoma (SCC),large-cell carcinoma (LC).

In a forty-third aspect, in accordance with any one of the precedingaspects from the 28^(th) to 42^(nd), the sample of biological fluidoriginates from a smoker individual who, at the moment of the collectionof the sample, presents a pulmonary tumour if subjected to imagingdiagnostic methods, in particular the smoker individual presentingnodules of dimensions of greater than 5 mm if subjected to a spiral CTscan.

In a forty-fourth aspect, a medical kit is provided for determiningbio-molecular markers present in a sample of human biological fluid, thekit comprising: a platform, for example a support for receiving fluidsamples, having a plurality of sites, each of which is destined toreceive a respective discrete quantity of the sample of biologicalfluid, each of the sites comprising a reagent capable of bonding with atleast a respective microRNA of Table Ia, Ic, IIa and/or Table IIc and/orTable Va, Vc, VIa and/or Table VIc, optionally a reagent capable ofbonding with at least a respective microRNA as in Table Ib, Id, IIband/or Table IId, and/or Table Vb, Vd, VIb and/or Table VId.

In a forty-fifth aspect in accordance with the preceding aspect, thereagent includes at least a reagent selected from among a groupcomprising:

a polynucleotide comprising a nucleotide sequence of at least one of themicroRNAs as in Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc,VIa and/or Table VIc, or a nucleotide sequence of at least one of themicroRNAs as in Table Ib, Id, IIb and/or Table IId, and/or Table Vb, Vd,VIb and/or Table VId;

a polynucleotide comprising a nucleotide sequence which is complementaryto a sequence of at least one of the microRNAs as in Table Ia, Ic, IIaand/or Table IIc and/or Table Va, Vc, VIa and/or Table VIc, optionallycomprising a nucleotide sequence which is complementary to a sequence ofat least one of the microRNAs as in Table Ib, Id, IIb and/or Table IId,and/or Table Vb, Vd, VIb and/or Table VId;

a molecular probe configured such as to recognize a sequence of at leastone of the microRNAs as in Table Ia, Ic, IIa and/or Table IIc and/orTable Va, Vc, VIa and/or Table VIc, optionally a sequence of at leastone of the microRNAs as in Table Ib, Id, IIb and/or Table IId, and/orTable Vb, Vd, VIb and/or Table VId.

In a forty-sixth aspect a medical apparatus is provided, comprising: aunit defining a seating for receiving one or more of the kits of thepreceding claim, means for determining a value of the level ofexpression of the microRNAs as in Tables Ia, Ic, IIa and/or Table IIcand/or Table Va, Vc, VIa and/or Table VIc, optionally the value of thelevel of expression of the microRNA as in Tables Ib, Id, IIb and/orTable IId, and/or Table Vb, Vd, VIb and/or Table VId; means forcalculating the values of the real ratios from among the values oflevels of expression of pairs of microRNAs, the ratios being selectedfrom those in Tables IIIa, IIIc, IVa and/or Table IVc and/or Table VIIa,VIII, VIIIa and/or Table VIIIc, optionally from those in Tables IIb,IIId, IVb and/or Table IVd and/or Table VIIb, VIId, VIIIb and/or TableVIIId.

In a forty-third aspect in accordance with the preceding aspect, themeans for determining the value of the level of expression comprise onefrom among the techniques selected from a group as follows: QuantitativeReal-time PCR, Microfluidic cards, Microarrays, RT-PCR, quantitative orsemi-quantitative, Northern blot, Solution Hybridization, or Sequencing.

In a forty-eighth aspect a method is comprised for treating anindividual in whom a presence of a pulmonary tumour has been diagnosedor in whom a risk of developing a pulmonary tumour has been identified,respectively for treatment of the pulmonary tumour or for reducingand/or eliminating the risk of developing a pulmonary tumour, the methodcomprising following steps: measuring a level of expression of at leastan miRNA listed in Table Ia, Ic, IIa and/or Table IIc and/or Table Va,Vc, VIa and/or Table VIc present in a sample of biological fluidpreviously taken from the individual, determining the miRNAs havingmeasured values of a level of expression which deviate with respect to apredetermined and respective control criterion; altering the level ofexpression of the miRNAs for which the levels of expression deviate withrespect to the respective control criterion.

In a forty-ninth aspect the step of measuring comprises measuring alevel of expression of at least a miRNA listed in Table Ib, Id, IIband/or Table IId, and/or Table Vb, Vd, VIb and/or Table VId present in asample of biological fluid previously taken from the individual.

In a fiftieth aspect in accordance with the preceding aspect the step ofaltering the level of expression of the miRNAs comprises: administeringto the individual an effective quantity of at least one of the miRNAslisted in Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc, VIaand/or Table VIc, or of one of more of the miRNA listed in Table Ib, Id,IIb and/or Table IId, and/or Table Vb, Vd, VIb and/or Table VId, if thelevel of expression measured of the miRNA or the miRNAs is lower than arespective control level of expression

In a fifty-first aspect according to the 49th or 50th aspect, the stepof altering the level of expression of the miRNAs comprisesadministering to the individual an effective quantity of at least acompound for inhibiting the expression of at least one of the miRNAslisted in Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc, VIaand/or Table VIc, or listed in Table Ib, Id, IIb and/or Table IId,and/or Table Vb, Vd, VIb and/or Table VId, if the measured level ofexpression of one or more of the miRNA or miRNAs is higher than thecontrol level of expression.

In a fifty-second aspect, in accordance with the 50^(th) aspect, themethod comprises restoring the values of levels of expression to acontrol level of expression for the miRNAs which are under-expressedwith respect to the respective control level of expression.

In a fifty-third aspect in accordance with any one of aspects from the48^(th) to the 52^(nd), the method comprises administering atherapeutically effective quantity of a compound comprising at least oneof the miRNAs of Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc,VIa and/or Table VIc, optionally at least one of the miRNA listed inTable Ib, Id, IIb and/or Table IId, and/or Table Vb, Vd, VIb and/orTable VId, chemically synthesized (miRNA mimetics) or recombinant.

In a fifty-fourth aspect according to any one of aspects from 51^(st) to53^(rd), the method comprises reducing the values of the level ofexpression to the control level of expression for miRNAs which areover-expressed with respect to the respective control level ofexpression.

In a fifty-fifth aspect in accordance with any one of the aspects from48^(th) to 54^(th), the method comprises administering a therapeuticallyeffective quantity of a compound comprising at least an inhibitor of amicroRNA of Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc, VIaand/or Table VIc or Table Ib, Id, IIb and/or Table IId, and/or Table Vb,Vd, VIb and/or Table VId.

In fifty-sixth aspect in accordance with the preceding aspect, theinhibitor comprises double-filament RNA.

In a fifty-seventh aspect according to the preceding aspect the methodcomprises short interfering RNA (siRNA), antisense nucleic acids(anti-miRNA oligonucleotides (AMOs), molecules of enzymatic RNA(ribozymes).

In a fifty-eight aspect according to any one of aspects from the 55^(th)to the 57^(th), the inhibitor is directed to a specific product ofmicroRNA and interferes with the expression, for example by means ofinhibition of a translation or induction of degradation, of a targetgene of the microRNA.

In a fifty-ninth aspect in accordance with any one of the precedingaspects, the step of determining the miRNAs having measured values ofthe levels of expression which deviate with respect to the respectivecontrol criterion comprises: calculating a plurality of real ratiosdetermined by performing a ratio between the measured values of thelevels of expression of a predetermined number of pairs of the microRNAmolecules, the ratios being selected from a group comprising the ratiosas in Table IIa, IIIc, IVa and/or Table IVc and/or Table VIIa, VIII,VIIIa and/or Table VIIIc, optionally the ratios being selected from agroup comprising the ratios as in and/or Table IIIb, IIId, IVb and/orTable IVd and/or Table VIIb, VIId, VIIIb and/or Table VIIId, determiningthe real ratios which deviate from the respective control values,identifying the miRNAs involved in the real ratios which deviate fromthe respective control value.

A sixtieth aspect concerns a pharmaceutical compound for treating anindividual in whom has been diagnosed a pulmonary tumour or in whom arisk of developing a pulmonary tumour has been identified, respectivelyfor treatment of the pulmonary tumour or for reducing and/or eliminatingthe risk of developing a pulmonary tumour, the compound comprising: atleast one, optionally at least six, of the miRNAs listed in Table Ia,Ic, IIa and/or Table IIc and/or Table Va, Vc, VIa and/or Table VIc,and/or at least an inhibitor of the expression of at least one,optionally at least six, of the miRNAs listed in Table Ia, Ic, IIaand/or Table IIc and/or Table Va, Vc, VIa and/or Table VIc.

In a sixty-first aspect, according to the preceding aspect, the compoundcomprises a therapeutically effective quantity of at least one of themiRNAs listed in Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc,VIa and/or Table VIc.

A sixty-second aspect concerns a pharmaceutical compound for treating anindividual in whom has been diagnosed a pulmonary tumour or in whom arisk of developing a pulmonary tumour has been identified, respectivelyfor treatment of the pulmonary tumour or for reducing and/or eliminatingthe risk of developing a pulmonary tumour, the compound comprising: atleast one, optionally at least six, of the miRNAs listed in Table Ib,Id, IIb and/or Table IId, and/or Table Vb, Vd, VIb and/or Table VId,and/or at least an inhibitor of the expression of at least one,optionally of at least six, of the miRNAs listed in Table Ib, Id, IIband/or Table Hd, and/or Table Vb, Vd, VIb and/or Table VId.

In a sixty-third aspect, according to the preceding aspect, the compoundcomprises a therapeutically effective quantity of at least one,optionally of at least six, of the miRNAs listed in Table Ib, Id, Ithand/or Table IId, and/or Table Vb, Vd, VIb and/or Table VId.

In a sixty-fourth aspect in accordance with any one of aspects from the60^(th) to the 63^(rd), the quantity is able, for the miRNAs that areunder-expressed with respect to the respective control level ofexpression, to restore the values of the level of expression to therespective control level of expression.

In a sixty-fifth aspect in accordance with any one of aspects from the60^(th) to the 64^(th), the therapeutically effective quantity comprisesmiRNA of Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc, VIaand/or Table VIc, optionally the therapeutically effective quantitycomprises the miRNA of Table Ib, Id, Ith and/or Table IId, and/or TableVb, Vd, VIb and/or Table VId, chemically synthesized or recombinant.

In a sixty-sixth aspect in accordance with any one of aspects from the60^(th) to the 64^(th), the compound comprises a therapeuticallyeffective quantity of the inhibitor of the expression of at least one ofthe miRNAs listed in Table Ia, Ic, IIa and/or Table IIc and/or Table Va,Vc, VIa and/or Table Vic, optionally all those listed in Table Ib, Id,IIb and/or Table IId, and/or Table Vb, Vd, VIb and/or Table VId, thequantity being able, for the over-expressed miRNAs with respect to therespective control level of expression, to reduce the values of thelevel of expression to the respective control level of expression.

In a sixty-seventh aspect in accordance with the preceding aspect, theinhibitor comprises double-filament RNA, optionally short interferingRNA (siRNA), and/or antisense nucleic acids, and/or enzymatic RNAmolecules (ribozymes).

In a sixty-eighth aspect in accordance with one of the preceding twoaspects, the inhibitor is directed to a specific product of microRNA andinterferes with the expression (by means of inhibition of translation orinduction of degradation) of a target gene of the microRNA.

In a sixty-ninth aspect, a pharmaceutical compound is provided accordingto any one of claims from the 60^(th) to the 68^(th), for preparation ofa medicament usable in one of the therapeutic methods of any one ofaspects from the 48^(th) to 59^(th).

In a seventieth aspect in accordance with the preceding aspect thetherapeutic method is a method for treating an individual in whom apresence of a pulmonary tumour has been diagnosed.

In a seventy-first aspect in accordance with the sixty-ninth, thetherapeutic method is a method for treating an individual in whom a riskof developing a pulmonary tumour has been identified, in order to reduceand/or eliminate the risk of developing the pulmonary tumour.

In a seventy-second aspect, in accordance with any one of the precedingaspects, as a variant of the invention and alternatively to the realratios (in the method, the medical kit and the apparatus) realdifferences are determined by performing the difference between themeasured values of the expression levels of a predetermined number ofpairs of the molecules of microRNA. In this case each of the differencesis compared with a respective control value in order to determine thedifferences which deviate from the respective control value.

All the preceding aspects are equally applied by replacing the realratios with real differences between the pairs of miRNA as in theappended tables.

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. In the specification, thesingular forms also include the plural unless the context clearlydictates otherwise. Although methods and materials similar or equivalentto those described herein can be used in the practice or testing of thepresent invention, suitable methods and materials are described below.All publications, patent applications, patents, and other referencesmentioned herein are incorporated by reference. The references citedherein are not admitted to be prior art to the claimed invention. In thecase of conflict, the present specification, including definitions, willcontrol. In addition, the materials, methods, and examples areillustrative only and are not intended to be limiting.

Other features and advantages of the invention will be apparent from thefollowing detailed description and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic showing the clinical-pathological characteristicsof patients from training and validation sets selected for miRNAexpression analysis in plasma samples.

FIG. 2 is a graph showing a Kaplan-Meier survival curve of patients withor without the signature of risk of aggressive disease.

FIG. 3 is a graph showing a Kaplan-Meier survival curve of patients withor without the signatures for presence of aggressive disease.

FIG. 4 is a series of ratios and graphs showing miRNA expressionanalyses in plasma samples collected before the onset and at the time ofdisease. The signatures of miRNA ratios and their direction in theanalyses are listed in the tables. Panel A shows miRNA signature of riskto develop lung cancer. Panel B shows miRNA signature of lung cancerdiagnosis. The ROC curves of samples belonging to the validation set areshown. Panel C shows Kaplan-Meier survival curves of patients with miRNAsignatures of risk of aggressive disease (RAD) in plasma samplescollected 1-2 y before CT-detection of lung cancer. Panel D showsKaplan-Meier survival curves of patients with miRNA signatures ofpresence of aggressive disease (PAD) in plasma samples collected at thetime of CT-detected lung cancer. The RAD- or PAD-positive patients showa significantly worse survival rate than RAD- or PAD-negative patients(P=0.0006 and P=0.0001, respectively).

FIG. 5 is two graphs showing the risk of manifesting a pulmonary tumor(validation set). Left Panel shows the ROC curve when using the 15miRNAs of Table Ito create the 30 ratios of Table III. Right Panel showsthe ROC curve when using the 6 miRNAs of Table Ib to create the 9 ratiosof Table IIb.

FIG. 6 is two graphs showing the risk of manifesting an aggressivepulmonary tumor (validation set). Left panel shows the ROC curve whenusing the 16 miRNAs of Table II to create the 28 ratios of Table IV.Right panel shows the ROC curve when using the 6 miRNAs of Table IIb tocreate the 9 ratios of Table IVb.

FIG. 7 is two graphs showing the risk of manifesting an aggressivepulmonary tumor (validation set). Left panel shows the ROC curve whenusing the 18 miRNAs of Table V to create the 36 ratios of Table VII.Right panel shows the ROC curve when using the 6 miRNAs of Table Vb tocreate the 9 ratios of Table VIIb.

FIG. 8 is two graphs showing the risk of manifesting an aggressivepulmonary tumor (validation set). Left panel shows the ROC curve whenusing the 10 miRNAs of Table VI to create the 16 ratios of Table VIII.Right panel shows the ROC curve when using the 6 miRNAs of Table VIb tocreate the 9 ratios of Table VIIIb.

FIG. 9 is a graph showing the expression levels of mir-486-5p andmir-660 in 20 paired tumor and normal lung tissue of the same patients.

FIG. 10 is a graph showing the results of a proliferation assayperformed on A549-GFP cells transfected with the miRNA mimic mir-486-5pand mir-660.

FIG. 11 is a graph showing the results of a migration assay performed onA549-GFP cells transfected with the miRNA mimic mir-486-5p and mir-660.

FIG. 12 is two graph showing Kaplan-Meier estimates of observed 5-ysurvival in CT-screening INT-IEO trial. Panel A shows data arrangedaccording to the extent of disease: 92% for stage I (95% CI: 70.0-97.8)and 7% for stage II-IV (95% CI: 0.5-27.5, P<0.001). Panel B shows dataarranged according to the year of CT-detection: 77% for lung cancersdetected in the first 2 y of the study (95% CI: 53.7-89.8) and 36% forlung cancers diagnosed from third to fifth years (95% CI: 13.7-58.7,P=0.005).

FIG. 13 is an illustration showing clustering analysis on 24 normal lungtissue samples using miRNAs differentially expressed between patientswith tumors detected in the first 2 y and those of later years ofscreening. Clinical status of the patient (0=alive, 1=dead), tumorstage, and year of tumor detection are reported in columns A, B, and C,respectively.

FIG. 14A is a diagram showing sample collection and analysis in thetraining set. FIG. 14B is a diagram showing sample collection andanalysis in the validation set. FIG. 14C is a diagram showing samplecollection and analysis in an enlarged data set.

FIG. 15 is a series of graphs showing consistency of miRNA expressionmeasurement in plasma samples by quantitative real-time PCR consideringonly the 100 miRNAs selected for class comparison analysis. Panel Ashows that technical duplicates were performed for two patient samples(341 and 380) and for a control pool (M2). The graphical representationwas performed plotting the first miRNA values obtained on abscissa(duplicate A) and the values obtained in the second evaluation inordinate (duplicate B). The linear regression value shows a goodreproducibility of measurements. Panel B shows the correlation betweentwo different control pools. Panel C is a graphical representation ofaverage values of all Pearson correlation coefficients between controlpools, technical duplicates, and between all patient samples (before andat time of disease.

FIG. 16A is graph showing the number of miRNA and ratio of miRNA for asignature of risk. FIG. 16B is graph showing the number of miRNA andratio of miRNA for a signature of aggressive risk. FIG. 16C is graphshowing the number of miRNA and ratio of miRNA for a signature ofdiagnosis. FIG. 16D is graph showing the number of miRNA and ratio ofmiRNA for a signature of aggressive disease.

FIG. 17 is a flow-chart illustrating the use of miRNA and the ratio ofmiRNA from a patient in the signatures of risk, aggressive risk,diagnosis and aggressive disease.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides methods comprising determining the levelof expression of at least two miRNA, or at least six miRNA, from themiRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc in abiological sample from a subject, and comparing the level of expressionof said miRNA from said sample from said subject to the level ofexpression of said miRNA from a control biological sample.

The present invention provides methods comprising determining the levelof expression of at least two miRNA, or at least six miRNA, listed inTable Ib or Id in a biological sample from a subject, and comparing thelevel of expression of said miRNA from said sample from said subject tothe level of expression of said miRNA from a control biological sample,wherein a change or deviation in the level of expression of said atleast two miRNA in said biological sample from said control biologicalsample identifies a subject at risk of manifesting a tumor. Preferably,the miRNA can be the miRNA listed in Table Ie. Preferably, the tumorcannot be detected by CT spiral scan.

The present invention provides methods comprising determining the levelof expression of at least two miRNA, or at least six miRNA, listed inTable IIb or IId in a biological sample from a subject, and comparingthe level of expression of said miRNA from said sample from said subjectto the level of expression of said miRNA from a control biologicalsample, wherein a change or deviation in the level of expression of saidat least two miRNA in said biological sample from said controlbiological sample identifies a subject at risk of manifesting anaggressive tumor. Preferably, the miRNA can be the miRNA listed inTables IIe, IIf or IIg.

The present invention provides methods comprising determining the levelof expression of at least two miRNA, or at least six miRNA, listed inTable Vb or Vd in a biological sample from a subject, and comparing thelevel of expression of said miRNA from said sample from said subject tothe level of expression of said miRNA from a control biological sample,wherein a change or deviation in the level of expression of said atleast two miRNA in said biological sample from said control biologicalsample determines the presence of a tumor in said subject. Preferably,the miRNA can be the miRNA listed in Tables Ve or Vf. Preferably, thedetermination of the presence of said tumor confirms detection by CTspiral scan.

The present invention provides methods comprising determining the levelof expression of at least two miRNA, or at least six miRNA, listed inTable VIb or VId in a biological sample from a subject, and comparingthe level of expression of said miRNA from said sample from said subjectto the level of expression of said miRNA from a control biologicalsample, wherein a change or deviation in the level of expression of saidat least two miRNA in said biological sample from said controlbiological sample determines the presence of an aggressive tumor in saidsubject. Preferably, the miRNA can be the miRNA listed in Tables VIe orVIf. Preferably, the determination provides a prognosis of disease-freesurvival following surgical intervention.

The methods of the present invention can further comprise calculating aplurality of real quotients by determining a ratio between the level ofexpression of at least one pair of miRNA from at least two miRNA, or atleast six miRNA, listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc;comparing each of the real quotients with a respective control value;and determining the real quotients which deviate from the respectivecontrol quotient value.

The methods of the present invention can further comprise calculating aplurality of real quotients by determining a ratio between the level ofexpression of at least one pair of miRNA from at least two miRNA, or atleast six miRNA, listed in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId;comparing each of the real quotients with a respective control value;and determining the real quotients which deviate from the respectivecontrol quotient value. Preferably, the miRNA can be the miRNA listed inTable Ie, IIe, IIf, IIg, Ve, Vf, VIe or VIf.

The methods of the present invention can further comprise determining anumber or percentage of real quotients which deviate from the respectivecontrol value.

The methods of the present invention can further comprise defining as anindividual at risk an individual for whom at least a predeterminednumber or a predetermined percentage of the real quotients deviates withrespect to the respective control quotient value.

For each of the calculated quotients a respective control quotient isassociated, represented by a ratio of the levels of expression for themiRNA in a control biological sample relative to a biological sample ofa same type.

The methods of the present invention can further comprise correlatingthe deviation of a predetermined number or a predetermined percentage oflevels of expression with respect to the corresponding control criteriato a presence or absence of risk that the individual might clinicallypresent with a tumor in a predetermined time.

The individual might clinically present an aggressive tumor in apredetermined time. The predetermined time is between one and threeyears. Preferably, the predetermined time is within 28 months.

Calculating the plurality of real quotients comprises using theexpression level of at least two miRNA, or at least six miRNA, listed inTables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc. Calculating the pluralityof real quotients comprises determining a predetermined number or apredetermined percentage of quotients from among the levels ofexpression, wherein the quotients are selected from at least one of thequotients, at least two of the quotients, at least six of the quotients,as listed in Tables IIa, IIc, IVa, IVc, VIIa, VIIc, VIIIa, or VIIIc. Atleast 20%, 30%, 50% or 100% of the real quotients listed in Tables IIIa,IIIc, IVa, IVc, VIIa, VIIc, VIIIa, or VIIIc can be determined Thequotients can be selected from the quotients as listed in Tables IIIb,IIId, IVb, IVd, VIIb, VIId, VIIIb, or VIIId.

The methods of the present invention can further comprise defining as anindividual at risk of a tumor, an individual for whom at least 20%, 30%,50% or 100% of the real quotients calculated deviate with respect to therespective control quotient value. The individual is at risk of a tumorbetween one to three years from a collection of the biological sample.The tumor can be an aggressive tumor.

The methods of the present invention can further comprise defining as anindividual presenting a tumor, an individual for whom at least 20%, 30%,50%, 60% or 100% of the real quotients calculated deviate with respectto the respective control quotient value. The tumor can be an aggressivetumor.

The tumor is a pulmonary tumor. The pulmonary tumor can be small-celllung cancer (SCLC), non small-cell lung cancer (NSCLC), pulmonaryadenocarcinoma (ADC), bronchio-alveolar carcinoma (BAC), squamous-celllung carcinoma (SCC) or large-cell carcinoma (LC).

The biological sample is a biological fluid. The biological fluid can bewhole blood, a fraction of blood, plasma or serum. The biological sampleoriginates from a smoker individual who, at the moment of the collectionof the sample, does not present a pulmonary tumor if subjected toimaging diagnostic methods, in particular the smoker individual notpresenting nodules of dimensions of greater than 5 mm if subjected to aspiral CT scan.

The control biological sample is a biological sample from a disease-freesubject. The control biological sample is a biological sample obtainedfrom said subject at a previous time. The control biological sample isobtained from said subject up to three years preceding diagnosis. Thecontrol biological sample is a biological sample obtained from adifferent tissue from said subject.

As used herein, an “individual”, “subject”, “patient” or “subject inneed thereof” is an individual having an risk of developing a tumor oran aggressive tumor or one who may have or may be afflicted with a tumoror aggressive tumor. These terms may be utilized interchangeably.Preferably, the individual is a mammal. The mammal can be e.g., anymammal, e.g., a human, primate, bird, mouse, rat, fowl, dog, cat, cow,horse, goat, camel, sheep or a pig. Preferably, the mammal is a human.

As used herein, MicroRNA or miRNA is small, non-coding, RNA molecules(length 19-25 nucleotides). In particular, reference is made to miRNApresent in biological samples of human tissue, for example whole blood,plasma, serum, saliva or bronchial condensate.

Signature of Risk

The present invention provides methods including: determining the levelof expression of the six miRNA listed in Table Ib or Id in a biologicalsample from a subject, and comparing the level of expression of saidmiRNA from said sample from said subject to the level of expression ofsaid miRNA from a control biological sample, wherein a change ordeviation in the level of expression of said at least six miRNA in saidbiological sample from said control biological sample identifies asubject at risk of manifesting a tumor. Preferably, the tumor cannot bedetected by CT spiral scan.

The method can further include: calculating a plurality of realquotients by determining a ratio between the level of expression of atleast one pair of miRNA from at least six miRNA listed in Table Ib orId; comparing each of the real quotients with a respective controlvalue; and determining the real quotients which deviate from therespective control quotient value.

The present invention provides miRNAs, in particular those of appendedTable Ia or Ic, as molecular biomarkers for the evaluation of the riskof manifesting pulmonary tumours within 1-3 years from the samplecollection of biological fluid. The present invention also provides thatthe ratios among the miRNA expression values are ideal molecularbiomarkers for investigation into the evaluation of the risk ofcontracting a pulmonary tumour within 1-3 years from the samplecollection of biological fluid, such as whole blood, serum, plasma,saliva or bronchial condensate.

As used herein, an individual at risk of tumour (aggressive or notaccording to the case studies): an individual who in the time ofreference (1-3 years) following the collection of the biological samplehas a risk of over 80% of developing a tumour, for example a pulmonarytumour, detectable using techniques such as spiral CT.

Using the expression levels of the miRNAs listed in Table Ia or Ic, theratios were identified among the values measured of the expressionlevels relative to the pairs of microRNA listed in Table IIIa or IIIc.These ratios can be used for the evaluation of the risk of contractingpulmonary tumour within 1-3 years from the collection of the sample ofbiological fluid, giving extremely reliable prediction results.

In more detail, by calculating a sufficient number of real ratiosselected from among those in Table IIIa or Inc, for example at least 20%of them, and optionally at least 50%, it is possible to observe theprogress with respect to control ratios. An individual is defined athigh risk of pulmonary tumour, which might be detectable by spiral CT,in a period comprised between one and three years from the collection ofthe sample of biological fluid, for whom at least 30% of real ratioscalculated deviates with respect to the respective value of the controlratio.

TABLE Ia One set of miRNAs used for evaluation of the risk ofmanifesting a pulmonary tumour (within 1-3 years from collecting thesample of biological fluid). miRNA hsa-miR-451 hsa-miR-320 hsa-miR-660hsa-miR-92a hsa-miR-106a hsa-miR-140-5p hsa-miR-15b hsa-miR-17hsa-miR-197 hsa-miR-19b hsa-miR-221 hsa-miR-28-3p hsa-miR-30bhsa-miR-30c hsa-miR-145

Comparing the miRNAs listed in Table Ia in pre-disease patient samplesv. disease free samples (control) results showed a sensitivity of 83.3(training sensitivity of 85.0; validation sensitivity of 81.3) and aspecificity of 95.5 (training specificity of 85.7; validationspecificity of 100.0).

TABLE Ib One set of preferred miRNAs used for evaluation of the risk ofmanifesting a pulmonary tumour (within 1-3 years from collecting thesample of biological fluid). miRNA hsa-miR-451 hsa-miR-320 hsa-miR-660hsa-miR-197 hsa-miR-30b hsa-miR-30c

Comparing the preferred miRNAs listed in Table Ib in pre-disease patientsamples v. disease free samples (control) results showed a sensitivityof 80.6 (training sensitivity of 80.0; validation sensitivity of 81.3)and a specificity of 95.5 (training specificity of 85.7; validationspecificity of 100.0).

TABLE Ic Another set of miRNAs used for evaluation of the risk ofmanifesting a pulmonary tumour (within 1-3 years from collecting thesample of biological fluid). miRNA hsa-miR-660 hsa-miR-451 hsa-miR-197hsa-miR-17 hsa-miR-15b hsa-miR-106a hsa-miR-16 hsa-miR-92a hsa-miR-19bhsa-miR-101 hsa-miR-133a hsa-miR-28-3p hsa-miR-320 hsa-miR-126hsa-miR-142-3p hsa-miR-140-3p

TABLE Id Another set of preferred miRNAs used for evaluation of the riskof manifesting a pulmonary tumour (within 1-3 years from collecting thesample of biological fluid). miRNA hsa-miR-660 hsa-miR-451 hsa-miR-197hsa-miR-17 hsa-miR-15b hsa-miR-106a

TABLE Ie Another set of preferred miRNAs used for evaluation of the riskof manifesting a pulmonary tumour (within 1-3 years from collecting thesample of biological fluid). miRNA hsa-miR-660 hsa-miR-197

TABLE IIIa ratios among measured values of expression of pairs of miRNAsused for evaluating a risk of manifesting a pulmonary tumour (within 1-3years from collecting the sample of biological fluid). miRNA Pairs Q1 =hsa-miR-30c/hsa-miR-660 Q2 = hsa-miR-30b/hsa-miR-660 Q3 =hsa-miR-197/hsa-miR-660 Q4 = hsa-miR-17/hsa-miR-660 Q5 =hsa-miR-28-3p/hsa-miR-660 Q6 = hsa-miR-106a/hsa-miR-660 Q7 =hsa-miR-15b/hsa-miR-660 Q8 = hsa-miR-30c/hsa-miR-451 Q9 =hsa-miR-30b/hsa-miR-451 Q10 = hsa-miR-197/hsa-miR-451 Q11 =hsa-miR-145/hsa-miR-660 Q12 = hsa-miR-19b/hsa-miR-660 Q13 =hsa-miR-17/hsa-miR-451 Q14 = hsa-miR-28-3p/hsa-miR-451 Q15 =hsa-miR-106a/hsa-miR-451 Q16 = hsa-miR-30c/hsa-miR-320 Q17 =hsa-miR-30b/hsa-miR-320 Q18 = hsa-miR-197/hsa-miR-320 Q19 =hsa-miR-15b/hsa-miR-451 Q20 = hsa-miR-28-3p/hsa-miR-320 Q21 =hsa-miR-197/hsa-miR-92a Q22 = hsa-miR-30b/hsa-miR-92a Q23 =hsa-miR-30c/hsa-miR-92a Q24 = hsa-miR-140-5p/hsa-miR-660 Q25 =hsa-miR-221/hsa-miR-660 Q26 = hsa-miR-19b/hsa-miR-451 Q27 =hsa-miR-145/hsa-miR-451 Q28 = hsa-miR-17/hsa-miR-320 Q29 =hsa-miR-106a/hsa-miR-320 Q30 = hsa-miR-15b/hsa-miR-320

TABLE IIIb ratios among measured values of expression of preferred pairsof microRNAs used for evaluating a risk of manifesting a pulmonarytumour (within 1-3 years from collecting the sample of biologicalfluid). miRNA Pairs hsa-miR-30b/hsa-miR-320 hsa-miR-30b/hsa-miR-451hsa-miR-30b/hsa-miR-660 hsa-miR-197/hsa-miR-451 hsa-miR-197/hsa-miR-660hsa-miR-197/hsa-miR-320 hsa-miR-30c/hsa-miR-451 hsa-miR-30c/hsa-miR-660hsa-miR-30c/hsa-miR-320

In connection with the risk of manifesting a pulmonary tumor, FIG. 5shows (on the left hand side) the ROC curve when using the 15 miRNAs ofTable Ia to create the 30 ratios of Table IIa and (on the right endside) the ROC curve when using the 6 miRNAs of Table Ib to create the 9ratios of Table IIIb.

TABLE IIIc Another set of ratios among measured values of expression ofpairs of miRNAs used for evaluating a risk of manifesting a pulmonarytumour (within 1-3 years from collecting the sample of biologicalfluid). miRNA Pairs < or > 3 y storage cut-off Q1 =hsa-miR-197/hsa-miR-660 > 3.44 Q2 = hsa-miR-197/hsa-miR-92a > −1.72 Q3 =hsa-miR-17/hsa-miR-660 > 8.63 Q4 = hsa-miR-17/hsa-miR-92a > 3.60 Q5 =hsa-miR-197/hsa-miR-451 > −2.45 Q6 = hsa-miR-17/hsa-miR-451 > 2.77 Q7 =hsa-miR-19b/hsa-miR-660 > 7.85 Q8 = hsa-miR-197/hsa-miR-19b > −3.96 Q9 =hsa-miR-19b/hsa-miR-451 > 1.90 Q10 = hsa-miR-106a/hsa-miR-660 > 8.71 Q11= hsa-miR-106a/hsa-miR-451 > 2.87 Q12 = hsa-miR-106a/hsa-miR-92a > 3.73Q13 = hsa-miR-101/hsa-miR-97 < −4.59 Q14 = hsa-miR-101/hsa-miR-17 <−9.73 Q15 = hsa-miR-133a/hsa-miR-660 > −0.11 Q16 =hsa-miR-133a/hsa-miR-451 > −5.49 Q17 = hsa-miR-101/hsa-miR-133a < −1.34Q18 = hsa-miR-16/hsa-miR-660 > 8.78 Q19 = hsa-miR-16/hsa-miR-451 > 2.38Q20 = hsa-miR-140-3p/hsa-miR-660 > −0.31 Q21 =hsa-miR-101/hsa-miR-140-3p < −0.11 Q22 = hsa-miR-15b/hsa-miR-451 > −1.40Q23 = hsa-miR-15b/hsa-miR-660 > 4.77 Q24 = hsa-miR-142-3p/hsa-miR-15b <2.71 Q25 = hsa-miR-126/hsa-miR-660 > 8.08 Q26 =hsa-miR-28-3p/hsa-miR-660 > 3.18 Q27 = hsa-miR-320/hsa-miR-660 > 6.39

Reducing the number of microRNAs and ratios (from the 27^(th) to the1^(st)), the shorter signatures were tested on the validation set,analyzing their power using the mean percent of correct classificationamong 6 different methods of class prediction analysis:, CompoundCovariate Predictor, Diagonal Linear Discriminant Analysis, 1-NearestNeighbor, 3-Nearest Neighbors, Nearest Centroid and Support VectorMachines. The results are shown in FIG. 16 a.

TABLE IIId Another set of ratios among measured values of expression ofpreferred pairs of microRNAs used for evaluating a risk of manifesting apulmonary tumour (within 1-3 years from collecting the sample ofbiological fluid). miRNA Pairs hsa-miR-197/hsa-miR-660hsa-miR-197/hsa-miR-92a hsa-miR-17/hsa-miR-660 hsa-miR-17/hsa-miR-92ahsa-miR-197/hsa-miR-451 hsa-miR-17/hsa-miR-451 hsa-miR-19b/hsa-miR-660hsa-miR-197/hsa-miR-19b hsa-miR-19b/hsa-miR-451

As used herein, miRNA ratios are real ratios determined by performing aratio among the measured values of the expression levels ofpredetermined pairs of molecules of microRNA.

Signature of Risk of Aggressive Disease

The present invention provides methods including: determining the levelof expression of the six miRNA listed in Table IIb or IId in abiological sample from a subject, and comparing the level of expressionof said miRNA from said sample from said subject to the level ofexpression of said miRNA from a control biological sample, wherein achange or deviation in the level of expression of said at least sixmiRNA in said biological sample from said control biological sampleidentifies a subject at risk of manifesting an aggressive tumor.Preferably, the tumor cannot be detected by CT spiral scan.

The method can further include: calculating a plurality of realquotients by determining a ratio between the level of expression of atleast one pair of miRNA from at least six miRNA listed in Table IIb orIId; comparing each of the real quotients with a respective controlvalue; and determining the real quotients which deviate from therespective control quotient value.

The present invention provides the miRNAs, in particular those ofappended Table IIa or IIc, as biomarkers for evaluation of the risk ofcontracting aggressive pulmonary tumour within 1-3 years from the samplecollection of biological fluid. Further, in this case too, the ratiosbetween the miRNA expression values were specifically identified asideal molecular biomarkers to be investigated for the evaluation of therisk of contracting an aggressive pulmonary tumour within 1-3 years fromthe sample biological fluid collection, which might be whole blood,serum, plasma, saliva or bronchial condensate.

Further, by using the miRNA expression levels of Table IIa or IIc, theratios were identified between measure values of expression levelsrelative to pairs of microRNAs of Table IVa or IVc for evaluation of therisk of contracting an aggressive pulmonary tumour within 1-3 years fromthe sample collection of biological fluid. In more detail, bycalculating a sufficient number of real ratios selected from among theratios of Table IVa or IVc, for example at least 30%, and optionally atleast 50%, the progression of the ratios with respect to control ratioscan be studied.

An individual is defined as at risk of contracting an aggressivepulmonary tumour in a period comprised between one and three years fromthe collection of the sample of biological fluid, if in that individualat least 50%, optionally at least 75%, of the real ratios calculateddeviate with respect to the respective control ratio value.

As used herein, an aggressive tumour is a tumour, for example apulmonary tumour, with a lethal prognosis or capable of causing death in90% of patients within five years from diagnosis of the disease.

The use of miRNA ratios also enables reliably predicting the developmentof pulmonary tumour, in particular of the more aggressive form, inhigh-risk individuals (more than 50 years of age and heavy smokers) upto two years before the disease is at a visible stage with the betterimaging techniques at present available (spiral CT). Note also that themethod using the calculation of the ratios, or miRNA ratios, describedabove can be actuated with a simple collection of a blood sample and istherefore entirely non-invasive, and allows the analysis to be performedrapidly and economically.

TABLE IIa microRNAs used for evaluation of the risk of manifesting anaggressive pulmonary tumour (within 1-3 years from collecting the sampleof biological fluid). miRNA hsa-miR-660 hsa-miR-140-5p hsa-miR-486-5phsa-miR-197 hsa-miR-221 hsa-miR-451 hsa-miR-28-3p hsa-miR-148ahsa-miR-19b hsa-miR-15b hsa-miR-30c hsa-miR-30b hsa-miR-101 hsa-miR-21hsa-miR-140-3p hsa-miR-142-3p

Comparing the miRNAs listed in Table IIa in pre-disease patient samplesof aggressive lung cancer v. pre-disease samples of indolent lung cancerand disease free samples (control) results showed a sensitivity of 94.5(training sensitivity of 90.9; validation sensitivity of 100.0) and aspecificity of 97.6 (training specificity of 100.0; validationspecificity of 96.0).

TABLE IIb preferred microRNAs used for evaluation of the risk ofmanifesting an aggressive pulmonary tumour (within 1-3 years fromcollecting the sample of biological fluid). miRNA hsa-miR-660hsa-miR-486-5p hsa-miR-221 hsa-miR-28-3p hsa-miR-148a hsa-miR-19b

Comparing the miRNAs listed in Table IIb in pre-disease patient samplesof aggressive lung cancer v. pre-disease samples of indolent lung cancerand disease free samples (control) results showed a sensitivity of 94.5(training sensitivity of 90.9; validation sensitivity of 100.0) and aspecificity of 95.0 (training specificity of 100.0; validationspecificity of 92.0).

TABLE IIc Another set of microRNAs used for evaluation of the risk ofmanifesting an aggressive pulmonary tumour (within 1-3 years fromcollecting the sample of biological fluid). miRNA hsa-miR-21 hsa-miR-451hsa-miR-197 hsa-miR-17 hsa-miR-15b hsa-miR-106a hsa-miR-16 hsa-miR-92ahsa-miR-19b hsa-miR-101 hsa-miR-145 hsa-miR-28-3p hsa-miR-30chsa-miR-320 hsa-miR-126 hsa-miR-221 hsa-miR-148a hsa-miR-30bhsa-miR-140-3p

TABLE IId Another set of preferred microRNAs used for evaluation of therisk of manifesting an aggressive pulmonary tumour (within 1-3 yearsfrom collecting the sample of biological fluid). miRNA hsa-miR-21hsa-miR-451 hsa-miR-197 hsa-miR-17 hsa-miR-15b hsa-miR-106a

TABLE IIe Another set of preferred microRNAs used for evaluation of therisk of manifesting an aggressive pulmonary tumour (within 1-3 yearsfrom collecting the sample of biological fluid). miRNA hsa-miR-197hsa-miR-451

TABLE IIf Another set of preferred microRNAs used for evaluation of therisk of manifesting an aggressive pulmonary tumour (within 1-3 yearsfrom collecting the sample of biological fluid). miRNA hsa-miR-197hsa-miR-101

TABLE IIg Another set of preferred microRNAs used for evaluation of therisk of manifesting an aggressive pulmonary tumour (within 1-3 yearsfrom collecting the sample of biological fluid). miRNA hsa-miR-197hsa-miR-28-3p hsa-miR-451 hsa-miR-101

TABLE IVa ratios among measured values of expression of pairs ofmicroRNAs used for determining a risk of manifesting an aggressivepulmonary tumour (within 1-3 years from collecting the sample ofbiological fluid). miRNA Pairs Q1 = hsa-miR-221/hsa-miR-660 Q2 =hsa-miR-221/hsa-miR-486-5p Q3 = hsa-miR-221/hsa-miR-451 Q4 =hsa-miR-140-3p/hsa-miR-221 Q5 = hsa-miR-21/hsa-miR-221 Q6 =hsa-miR-101/hsa-miR-221 Q7 = hsa-miR-197/hsa-miR-660 Q8 =hsa-miR-197/hsa-miR-486-5p Q9 = hsa-miR-140-5p/hsa-miR-660 Q10 =hsa-miR-140-5p/hsa-miR-486-5p Q11 = hsa-miR-140-5p/hsa-miR-19b Q12 =hsa-miR-142-3p/hsa-miR-660 Q13 = hsa-miR-148a/hsa-miR-660 Q14 =hsa-miR-148a/hsa-miR-486-5p Q15 = hsa-miR-148a/hsa-miR-19b Q16 =hsa-miR-148a/hsa-miR-451 Q17 = hsa-miR-15b/hsa-miR-660 Q18 =hsa-miR-15b/hsa-miR-486-5p Q19 = hsa-miR-15b/hsa-miR-19b Q20 =hsa-miR-19b/hsa-miR-221 Q21 = hsa-miR-19b/hsa-miR-30c Q22 =hsa-miR-28-3p/hsa-miR-660 Q23 = hsa-miR-28-3p/hsa-miR-486-5p Q24 =hsa-miR-30b/hsa-miR-660 Q25 = hsa-miR-30b/hsa-miR-486-5p Q26 =hsa-miR-30c/hsa-miR-660 Q27 = hsa-miR-30c/hsa-miR-486-5p Q28 =hsa-miR-19b/hsa-miR-28-3p

TABLE IVb ratios among measured values of expression of preferred pairsof microRNAs used for determining a risk of manifesting an aggressivepulmonary tumour (within 1-3 years from collecting the sample ofbiological fluid). miRNA Pairs hsa-miR-221/hsa-miR-660hsa-miR-28-3p/hsa-miR-660 hsa-miR-19b/hsa-miR-221hsa-miR-19b/hsa-miR-28-3p hsa-miR-148a/hsa-miR-19bhsa-miR-148a/hsa-miR-486-5p hsa-miR-28-3p/hsa-miR-486-5phsa-miR-221/hsa-miR-486-5p hsa-miR-148a/hsa-miR-660

In connection with the risk of manifesting an aggressive pulmonarytumor, FIG. 6 shows (on the left hand side) the ROC curve when using the16 miRNAs of Table IIa to create the 28 ratios of Table IVa and (on theright end side) the ROC curve when using the 6 miRNAs of Table IIb tocreate the 9 ratios of Table IVb.

TABLE IVc Another set of ratios among measured values of expression ofpairs of microRNAs used for determining a risk of manifesting anaggressive pulmonary tumour (within 1-3 years from collecting the sampleof biological fluid). miRNA Pairs < or > 3y storage cut-off Q1 =hsa-miR-101/hsa-miR-197 < −4.51 Q2 = hsa-miR-197/hsa-miR-451 > −2.07 Q3= hsa-miR-101/hsa-miR-28-3p < −4.42 Q4 = hsa-miR-28-3p/hsa-miR-451 >−2.36 Q5 = hsa-miR-197/hsa-miR-21 > −0.38 Q6 = hsa-miR-21/hsa-miR-28-3p< 0.78 Q7 = hsa-miR-101/hsa-miR-106a < −9.85 Q8 =hsa-miR-106a/hsa-miR-451 > 3.14 Q9 = hsa-miR-106a/hsa-miR-21 > 4.81 Q10= hsa-miR-16/hsa-miR-28-3p < 4.72 Q11 = hsa-miR-16/hsa-miR-197 < 4.56Q12 = hsa-miR-106a/hsa-miR-16 > 0.66 Q13 = hsa-miR-101/hsa-miR-17 <−9.74 Q14 = hsa-miR-17/hsa-miR-451 > 3.04 Q15 = hsa-miR-17/hsa-miR-21 >4.67 Q16 = hsa-miR-16/hsa-miR-17 < −0.56 Q17 =hsa-miR-28-3p/hsa-miR-92a > −1.6 Q18 = hsa-miR-197/hsa-miR-92a > −1.36Q19 = hsa-miR-197/hsa-miR-30c > −1.51 Q20 = hsa-miR-28-3p/hsa-miR-30c >−1.79 Q21 = hsa-miR-320/hsa-miR-92a > 1.42 Q22 =hsa-miR-320/hsa-miR-451 > 0.66 Q23 = hsa-miR-221/hsa-miR-451 > −0.2 Q24= hsa-miR-21/hsa-miR-221 < −1.33 Q25 = hsa-miR-145/hsa-miR-197 < −0.96Q26 = hsa-miR-145/hsa-miR-28-3p < −0.69 Q27 =hsa-miR-28-3p/hsa-miR-30b > −3.47 Q28 = hsa-miR-197/hsa-miR-30b > −3.2Q29 = hsa-miR-19b/hsa-miR-451 > 2.19 Q30 = hsa-miR-126/hsa-miR-451 >2.24 Q31 = hsa-miR-15b/hsa-miR-451 > −1.2 Q32 = hsa-miR-148a/hsa-miR-197< −3.38 Q33 = hsa-miR-140-3p/hsa-miR-451 > −6.81

Reducing the number of microRNAs and ratios (from the 33^(rd) to the1^(st)), the shorter signatures were tested on the validation set,analyzing their power using the mean percent of correct classificationamong 6 different methods of class prediction analysis:, CompoundCovariate Predictor, Diagonal Linear Discriminant Analysis, 1-NearestNeighbor, 3-Nearest Neighbors, Nearest Centroid and Support VectorMachines. The results are shown in FIG. 16 b.

TABLE IVd Another set of ratios among measured values of expression ofpreferred pairs of microRNAs used for determining a risk of manifestingan aggressive pulmonary tumour (within 1-3 years from collecting thesample of biological fluid). miRNA Pairs hsa-miR-101/hsa-miR-197hsa-miR-197/hsa-miR-451 hsa-miR-101/hsa-miR-28-3phsa-miR-28-3p/hsa-miR-451 hsa-miR-197/hsa-miR-21hsa-miR-21/hsa-miR-28-3p hsa-miR-101/hsa-miR-106ahsa-miR-106a/hsa-miR-451 hsa-miR-106a/hsa-miR-21

Signature of Diagnosis

The present invention provides a method including: determining the levelof expression of the six miRNA listed in Table Vb or Vd in a biologicalsample from a subject, and comparing the level of expression of saidmiRNA from said sample from said subject to the level of expression ofsaid miRNA from a control biological sample, wherein a change ordeviation in the level of expression of said at least six miRNA in saidbiological sample from said control biological sample determines thepresence of a tumor in said subject. Preferably, determination of thepresence of said tumor confirms detection by CT spiral scan.

The method can further include: calculating a plurality of realquotients by determining a ratio between the level of expression of atleast one pair of miRNA from at least six miRNA listed in Table Vb orVd; comparing each of the real quotients with a respective controlvalue; and determining the real quotients which deviate from therespective control quotient value.

The present invention provides miRNAs, and in particular those listed inTable Va or Vc, have a role as biomolecular markers for determining theactual presence of a pulmonary tumour in an individual, for diagnosticpurposes.

The present invention also provides the ratios between expression levelvalues of miRNA pairs are valid biomarkers with a diagnostic andprognostic function. In detail, the miRNAs of Table Va or Vc were usedfor determining the ratios of Table VIIa or VIIc which represent ratiosbetween measured values of expression levels of relative microRNA pairsand which are used to determine the actual presence (diagnosis) of apulmonary tumour in an individual. In more detail, by calculating atleast 20% of the real ratios of Table VIIa or VIIc it is possible todefine the individual presents a pulmonary tumour if at least 30% of thereal ratios (as in Table VIIa or VIIc) calculated deviate from therespective control value.

TABLE Va microRNAs used for determining the actual presence of apulmonary tumour in an individual. miRNA hsa-miR-106a hsa-miR-140-3phsa-miR-17 hsa-miR-660 hsa-miR-15b hsa-miR-92a hsa-miR-451 hsa-miR-19bhsa-miR-28-3p hsa-miR-133a hsa-miR-101 hsa-miR-197 hsa-miR-145hsa-miR-320 hsa-miR-21 hsa-miR-30b hsa-miR-126 hsa-miR-140-5p

Comparing the miRNAs listed in Table Va in the plasma of patients atsurgery v. disease free samples (control) results showed a sensitivityof 80.5 (training sensitivity of 84.2; validation sensitivity of 76.5)and a specificity of 95.5 (training specificity of 100.0; validationspecificity of 93.3).

TABLE Vb preferred microRNAs used for determining the actual presence ofa pulmonary tumour in an individual. miRNA hsa-miR-106a hsa-miR-17hsa-miR-660 hsa-miR-92a hsa-miR-451 hsa-miR-197

Comparing the miRNAs listed in Table Vb in the plasma of patients atsurgery v. disease free samples (control) results showed a sensitivityof 77.8 (training sensitivity of 84.2; validation sensitivity of 70.6)and a specificity of 90.9 (training specificity of 85.7; validationspecificity of 93.3).

TABLE Vc Another set of microRNAs used for determining the actualpresence of a pulmonary tumour in an individual. miRNA hsa-miR-660hsa-miR-197 hsa-miR-17 hsa-miR-106a hsa-miR-142-3p hsa-miR-92ahsa-miR-19b hsa-miR-101 hsa-miR-145 hsa-miR-28-3p hsa-miR-320hsa-miR-126 hsa-miR-140-5p hsa-miR-148

TABLE Vd Another set of preferred microRNAs used for determining theactual presence of a pulmonary tumour in an individual. miRNAhsa-miR-660 hsa-miR-197 hsa-miR-17 hsa-miR-106a hsa-miR-142-3phsa-miR-92a

TABLE Ve Another set of preferred microRNAs used for determining theactual presence of a pulmonary tumour in an individual. miRNAhsa-miR-660 hsa-miR-197

TABLE Vf Another set of preferred microRNAs used for determining theactual presence of a pulmonary tumour in an individual. miRNAhsa-miR-197 hsa-miR-106a hsa-miR-660 hsa-miR-92a

TABLE VIIa ratios among measured values of expression of pairs ofmicroRNAs used for determining an actual presence of pulmonary tumour inan individual. miRNA Pairs Q1 = hsa-miR-17/hsa-miR-451 Q2 =hsa-miR-106a/hsa-miR-451 Q3 = hsa-miR-133a/hsa-miR-451 Q4 =hsa-miR-17/hsa-miR-660 Q5 = hsa-miR-106a/hsa-miR-660 Q6 =hsa-miR-197/hsa-miR-451 Q7 = hsa-miR-133a/hsa-miR-660 Q8 =hsa-miR-145/hsa-miR-451 Q9 = hsa-miR-28-3p/hsa-miR-451 Q10 =hsa-miR-17/hsa-miR-92a Q11 = hsa-miR-106a/hsa-miR-92a Q12 =hsa-miR-197/hsa-miR-660 Q13 = hsa-miR-133a/hsa-miR-92a Q14 =hsa-miR-145/hsa-miR-660 Q15 = hsa-miR-28-3p/hsa-miR-660 Q16 =hsa-miR-15b/hsa-miR-451 Q17 = hsa-miR-19b/hsa-miR-451 Q18 =hsa-miR-30b/hsa-miR-451 Q19 = hsa-miR-17/hsa-miR-320 Q20 =hsa-miR-106a/hsa-miR-320 Q21 = hsa-miR-17/hsa-miR-21 Q22 =hsa-miR-106a/hsa-miR-21 Q23 = hsa-miR-197/hsa-miR-92a Q24 =hsa-miR-101/hsa-miR-106a Q25 = hsa-miR-133a/hsa-miR-320 Q26 =hsa-miR-101/hsa-miR-17 Q27 = hsa-miR-145/hsa-miR-92a Q28 =hsa-miR-28-3p/hsa-miR-92a Q29 = hsa-miR-106a/hsa-miR-140-3p Q30 =hsa-miR-15b/hsa-miR-660 Q31 = hsa-miR-19b/hsa-miR-660 Q32 =hsa-miR-30b/hsa-miR-660 Q33 = hsa-miR-126/hsa-miR-451 Q34 =hsa-miR-140-5p/hsa-miR-451 Q35 = hsa-miR-133a/hsa-miR-21 Q36 =hsa-miR-140-3p/hsa-miR-17

TABLE VIIb ratios among measured values of expression of preferred pairsof microRNAs used for determining an actual presence of pulmonary tumourin an individual. miRNA Pairs hsa-miR-106a/hsa-miR-660hsa-miR-106a/hsa-miR-92a hsa-miR-106a/hsa-miR-451 hsa-miR-17/hsa-miR-451hsa-miR-17/hsa-miR-660 hsa-miR-17/hsa-miR-92a hsa-miR-197/hsa-miR-451hsa-miR-197/hsa-miR-92a hsa-miR-197/hsa-miR-660

In connection with the determination of the actual presence of apulmonary tumour in an individual, FIG. 7 shows (on the left hand side)the ROC curve when using the 18 miRNAs of Table Va to create the 36ratios of Table VIIa and (on the right end side) the ROC curve whenusing the 6 miRNAs of Table Vb to create the 9 ratios of Table VIIb.

TABLE VIIc Another set of ratios among measured values of expression ofpairs of microRNAs used for determining an actual presence of pulmonarytumour in an individual. miRNA Pairs < or > 3y storage cut-off Q1 =hsa-miR-197/hsa-miR-660 > 3.58 Q2 = hsa-miR-197/hsa-miR-92a > −1.5 Q3 =hsa-miR-106a/hsa-miR-92a > 3.73 Q4 = hsa-miR-106a/hsa-miR-660 > 8.87 Q5= hsa-miR-106a/hsa-miR-197 < 4.97 Q6 = hsa-miR-142-3p/hsa-miR-197 < 3.73Q7 = hsa-miR-140-5p/hsa-miR-197 < −0.03 Q8 =hsa-miR-142-3p/hsa-miR-28-3p < 4.19 Q9 = hsa-miR-140-5p/hsa-miR-28-3p <0.33 Q10 = hsa-miR-28-3p/hsa-miR-660 > 3.18 Q11 =hsa-miR-28-3p/hsa-miR-92a > −1.79 Q12 = hsa-miR-17/hsa-miR-660 > 8.63Q13 = hsa-miR-17/hsa-miR-92a > 3.6 Q14 = hsa-miR-142-3p/hsa-miR-145 <3.94 Q15 = hsa-miR-145/hsa-miR-660 > 3.76 Q16 =hsa-miR-145/hsa-miR-92a > −1.35 Q17 = hsa-miR-197/hsa-miR-320 > −2.45Q18 = hsa-miR-106a/hsa-miR-320 > 2.79 Q19 = hsa-miR-17/hsa-miR-320 >2.64 Q20 = hsa-miR-148a/hsa-miR-92a > −4.41 Q21 =hsa-miR-148a/hsa-miR-660 > 0.76 Q22 = hsa-miR-19b/hsa-miR-660 > 7.95 Q23= hsa-miR-19b/hsa-miR-92a > 2.75 Q24 = hsa-miR-101/hsa-miR-660 > −0.08Q25 = hsa-miR-101/hsa-miR-92a > −5.18 Q26 = hsa-miR-126/hsa-miR-660 >8.08 Q27 = hsa-miR-126/hsa-miR-92a > 3.05

Reducing the number of microRNAs and ratios (from the 27^(th) to the1^(st)), the shorter signatures were tested on the validation set,analyzing their power using the mean percent of correct classificationamong 6 different methods of class prediction analysis:, CompoundCovariate Predictor, Diagonal Linear Discriminant Analysis, 1-NearestNeighbor, 3-Nearest Neighbors, Nearest Centroid and Support VectorMachines. The results are shown in FIG. 16 c.

TABLE VIId Another set of ratios among measured values of expression ofpreferred pairs of microRNAs used for determining an actual presence ofpulmonary tumour in an individual. miRNA Pairs hsa-miR-197/hsa-miR-660hsa-miR-197/hsa-miR-92a hsa-miR-106a/hsa-miR-92ahsa-miR-106a/hsa-miR-660 hsa-miR-106a/hsa-miR-197hsa-miR-142-3p/hsa-miR-197 hsa-miR-140-5p/hsa-miR-197hsa-miR-142-3p/hsa-miR-28-3p hsa-miR-140-5p/hsa-miR-28-3phsa-miR-28-3p/hsa-miR-660 hsa-miR-28-3p/hsa-miR-92a

Signature of Presence of Aggressive Disease

The present invention provides a method including: determining the levelof expression of the six miRNA listed in Table VIb or VId in abiological sample from a subject, and comparing the level of expressionof said miRNA from said sample from said subject to the level ofexpression of said miRNA from a control biological sample, wherein achange or deviation in the level of expression of said at least sixmiRNA in said biological sample from said control biological sampledetermines the presence of an aggressive tumor in said subject.Preferably, the determination provides a prognosis of disease-freesurvival following surgical intervention.

The method can further include: calculating a plurality of realquotients by determining a ratio between the level of expression of atleast one pair of miRNA from at least six miRNA listed in Table VIb orVId; comparing each of the real quotients with a respective controlvalue; and determining the real quotients which deviate from therespective control quotient value.

The present invention provides miRNAs, and in particular those listed inTable VIa or VIc, that can be used as biomolecular markers fordetermining the actual presence of an aggressive pulmonary tumour in anindividual (prognosis). The present invention demonstrates in particularthe ratios between values of expression levels of miRNA pairs are validbiomarkers with a diagnostic and prognostic function even in the case ofan aggressive tumour.

In detail, the miRNAs of Table VIa and VIc were used to determine theratios of Table VIIIa and VIIIc where there is a list of ratios betweenthe measured values of the expression levels relative to microRNA pairsof Table VIa and VIc used for determining the actual presence of anaggressive pulmonary tumour in an individual. In detail, by detecting atleast 20% of the real ratios of Table VIIIa and VIIIc, it is possible todefine an individual having an aggressive pulmonary tumour as one inwhom at least 60% of the real ratios that have been calculated deviatewith respect to the respective control value.

Thus the use of the described procedure can help also to resolve theproblem of overdiagnosis and overtreatment in patients who are not atrisk.

In greater detail, in a context of surveillance of the disease usingspiral CT, the use of a test based on this method might enable selectionof only a sub-group of patients at high risk of developing the diseaseto be subsequently kept under a more strict control. Further, theability of the test to predict the patients who will develop a moreaggressive disease, frequently not diagnosed by the CT scan, enablesdirecting these individuals directly to specific pharmacologicalprogrammes (including giving up smoking) and/or the use of more specificdiagnostic examinations based on the metabolic-biologicalcharacteristics such as PET with various tracers or body MRI, or adifferent local treatment such as stereotaxic radiotherapy, or othertreatments besides. The use of miRNA ratios is an easily-applicablemethod with a potential current clinical use and which avoids the use ofmore profound and complex analysis.

TABLE VIa microRNAs used for determining the actual presence of anaggressive pulmonary tumour in an individual. miRNA hsa-miR-142-3phsa-miR-148a hsa-miR-15b hsa-miR-21 hsa-miR-221 hsa-miR-660 hsa-miR-19bhsa-miR-486-5p hsa-miR-30b hsa-miR-16

Comparing the miRNAs listed in Table VIa in patient samples ofaggressive lung cancer v. pre-disease samples of indolent lung cancerand disease free samples (control) results showed a sensitivity of 86.7(training sensitivity of 80.0; validation sensitivity of 100.0) and aspecificity of 93.2 (training specificity of 94.0; validationspecificity of 92.6).

TABLE VIb preferred microRNAs used for determining the actual presenceof an aggressive pulmonary tumour in an individual. miRNA hsa-miR-142-3phsa-miR-21 hsa-miR-221 hsa-miR-660 hsa-miR-19b hsa-miR-486-5p

Comparing the miRNAs listed in Table VIb in patient samples ofaggressive lung cancer v. pre-disease samples of indolent lung cancerand disease free samples (control) results showed a sensitivity of 80.0(training sensitivity of 80.0; validation sensitivity of 80.0) and aspecificity of 93.2 (training specificity of 94.0; validationspecificity of 92.6).

TABLE VIc Another set of microRNAs used for determining the actualpresence of an aggressive pulmonary tumour in an individual. miRNAhsa-miR-660 hsa-miR-197 hsa-miR-17 hsa-miR-106a hsa-miR-142-3phsa-miR-92a hsa-miR-19b hsa-miR-101 hsa-miR-145 hsa-miR-28-3phsa-miR-451 hsa-miR-126 hsa-miR-140-5p hsa-miR-148a hsa-miR-486-5phsa-miR-21 hsa-miR-16 hsa-miR-30b hsa-miR-30c hsa-miR-15b

TABLE VId Another set of preferred microRNAs used for determining theactual presence of an aggressive pulmonary tumour in an individual.miRNA hsa-miR-660 hsa-miR-197 hsa-miR-17 hsa-miR-106a hsa-miR-142-3phsa-miR-92a

TABLE VIe Another set of preferred microRNAs used for determining theactual presence of an aggressive pulmonary tumour in an individual.miRNA hsa-miR-451 hsa-miR-197

TABLE VIf Another set of preferred microRNAs used for determining theactual presence of an aggressive pulmonary tumour in an individual.miRNA hsa-miR-197 hsa-miR-486-5p hsa-miR-451

TABLE VIIIa ratios among measured values of expression of pairs ofmicroRNAs used for determining an actual presence of aggressivepulmonary tumour in an individual. miRNA Pairs Q1 =hsa-miR-142-3p/hsa-miR-486-5p Q2 = hsa-miR-21/hsa-miR-486-5p Q3 =hsa-miR-221/hsa-miR-486-5p Q4 = hsa-miR-19b/hsa-miR-21 Q5 =hsa-miR-19b/hsa-miR-221 Q6 = hsa-miR-142-3p/hsa-miR-19b Q7 =hsa-miR-148a/hsa-miR-486-5p Q8 = hsa-miR-15b/hsa-miR-486-5p Q9 =hsa-miR-30b/hsa-miR-486-5p Q10 = hsa-miR-142-3p/hsa-miR-660 Q11 =hsa-miR-221/hsa-miR-660 Q12 = hsa-miR-148a/hsa-miR-19b Q13 =hsa-miR-15b/hsa-miR-19b Q14 = hsa-miR-19b/hsa-miR-30b Q15 =hsa-miR-16/hsa-miR-486-5p Q16 = hsa-miR-21/hsa-miR-660

TABLE VIIIb ratios among measured values of expression of preferredpairs of microRNAs used for determining an actual presence of aggressivepulmonary tumour in an individual. miRNA Pairs Q1 =hsa-miR-hsa-miR-142-3p/hsa-miR-660 hsa-miR-142-3p/hsa-miR-19bhsa-miR-21/hsa-miR-660 hsa-miR-221/hsa-miR-660 hsa-miR-19b/hsa-miR-21hsa-miR-19b/hsa-miR-221 hsa-miR-142-3p/hsa-miR-486-5phsa-miR-221/hsa-miR-486-5p hsa-miR-21/hsa-miR-486-5p

In connection with the determination of the actual presence of anaggressive pulmonary tumour in an individual, FIG. 8 shows (on the lefthand side) the ROC curve when using the 10 miRNAs of Table VIa to createthe 16 ratios of Table VIIIa and (on the right end side) the ROC curvewhen using the 6 miRNAs of Table VIb to create the 9 ratios of TableVIIIb.

TABLE VIIIc Another set of ratios among measured values of expression ofpairs of microRNAs used for determining an actual presence of aggressivepulmonary tumour in an individual. miRNA Pairs < or > 3y storage cut-offQ1 = hsa-miR-197/hsa-miR-451 > −1.76 Q2 = hsa-miR-197/hsa-miR-486-5p >−1.65 Q3 = hsa-miR-106a/hsa-miR-197 < 4.9 Q4 =hsa-miR-106a/hsa-miR-486-5p > 3.59 Q5 = hsa-miR-106a/hsa-miR-451 > 3.14Q6 = hsa-miR-17/hsa-miR-197 < 4.79 Q7 = hsa-miR-17/hsa-miR-486-5p > 3.49Q8 = hsa-miR-17/hsa-miR-451 > 3.21 Q9 = hsa-miR-126/hsa-miR-197 < 4.17Q10 = hsa-miR-126/hsa-miR-486-5p > 2.75 Q11 = hsa-miR-126/hsa-miR-451 >2.58 Q12 = hsa-miR-197/hsa-miR-660 > 4.59 Q13 =hsa-miR-126/hsa-miR-660 > 8.46 Q14 = hsa-miR-28-3p/hsa-miR-660 > 3.53Q15 = hsa-miR-28-3p/hsa-miR-486-5p > −2.41 Q16 =hsa-miR-28-3p/hsa-miR-451 > −2.36 Q17 = hsa-miR-197/hsa-miR-19b > −3.97Q18 = hsa-miR-19b/hsa-miR-486-5p > 2.41 Q19 = hsa-miR-19b/hsa-miR-660 >8.42 Q20 = hsa-miR-19b/hsa-miR-451 > 2.19 Q21 =hsa-miR-140-5p/hsa-miR-197 < −0.52 Q22 = hsa-miR-140-5p/hsa-miR-28-3p <0.28 Q23 = hsa-miR-16/hsa-miR-197 < 4.48 Q24 = hsa-miR-197/hsa-miR-92a >−1.14 Q25 = hsa-miR-101/hsa-miR-197 < −4.51 Q26 =hsa-miR-145/hsa-miR-451 > −2 Q27 = hsa-miR-148a/hsa-miR-451 > −4.77 Q28= hsa-miR-142-3p/hsa-miR-197 < 3 Q29 = hsa-miR-30b/hsa-miR-451 > 1.2 Q30= hsa-miR-15b/hsa-miR-451 > −1.2 Q31 = hsa-miR-30c/hsa-miR-451 > −0.3Q32 = hsa-miR-197/hsa-miR-21 > −0.21

Reducing the number of microRNAs and ratios (from the 32^(nd) to the1^(st)), the shorter signatures were tested on the validation set,analyzing their power using the mean percent of correct classificationamong 6 different methods of class prediction analysis: CompoundCovariate Predictor, Diagonal Linear Discriminant Analysis, 1-NearestNeighbor, 3-Nearest Neighbors, Nearest Centroid and Support VectorMachines. The results are shown in FIG. 16 d.

TABLE VIIId Another set of ratios among measured values of expression ofpreferred pairs of microRNAs used for determining an actual presence ofaggressive pulmonary tumour in an individual. miRNA Pairshsa-miR-197/hsa-miR-451 hsa-miR-197/hsa-miR-486-5phsa-miR-106a/hsa-miR-197 hsa-miR-106a/hsa-miR-486-5phsa-miR-106a/hsa-miR-451 hsa-miR-17/hsa-miR-197hsa-miR-17/hsa-miR-486-5p hsa-miR-17/hsa-miR-451 hsa-miR-126/hsa-miR-197hsa-miR-126/hsa-miR-486-5p hsa-miR-126/hsa-miR-451

Once the miRNA profile of the subject is obtained, it is necessary todetermine for each ratio if the value exceed a predetermined cut-offvalue. The results from the training and validation set show that forthe signatures of risk and diagnosis, described above in Tables 111c andVIIc, respectively, at least 30% (e.g., about 10 out of 27) of theratios must exceed the cut-off to consider the subject positive for thetest. For the two signatures of aggressiveness, described above inTables IVc and VIIIc, respectively, at least 50% (e.g., 17 out of 33 and17 out of 32) of the ratios must exceed the cut-off to consider thepatient positive for the signature of aggressive risk and presence ofaggressive disease, respectively. When reducing the number of miRNAscomposing the signature the percentage of positive ratios must be thesame. The cut-off values were obtained with the validation set fromsamples stored for almost 3 years, and the values are shown in Tables111c, IVc, VIIc and VIIIc.

If a subject is determined to be positive to more than one signature,the most critical one is considered in this order: risk, diagnosis (bothlow risk), risk of aggressive disease, presence of aggressive disease(both high risk). A flow chart is shown in FIG. 17.

Compositions and Methods of Treatment

The method can further comprise altering the level of expression of atleast one miRNA, at least two miRNA or at least six miRNA, for which thelevel of expression changes or deviates, thereby reducing or eliminatingthe risk of developing a tumor in said subject. The method can furthercomprise altering the level of expression of at least one miRNA, atleast two miRNA or at least six miRNA, for which the level of expressionchanges or deviates, thereby reducing or eliminating the risk ofdeveloping an aggressive tumor in said subject. The method can furthercomprise altering the level of expression of at least one miRNA, atleast two miRNA or at least six miRNA, for which the level of expressionchanges or deviates, thereby treating a tumor in said subject. Themethod can further comprise altering the level of expression of at leastone miRNA, at least two miRNA or at least six miRNA, for which the levelof expression changes or deviates, thereby treating an aggressive tumorin said subject.

Preferably, altering the level of expression of said of at least onemiRNA, at least two miRNA or at least six miRNA, comprises administeringto said subject a therapeutically effective amount of at least onemiRNA, at least two miRNA or at least six miRNA, listed in Tables Ia,Ic, IIa, IIc, Va, Vc, VIa, or VIc, or a chemically synthesized miRNAmimetic or recombinant thereof, if the level of expression of said of atleast one miRNA, at least two miRNA or at least six miRNA, is lower thanthe control level of expression or administering to said subject atherapeutically effective amount of a compound capable of inhibiting theexpression of at least one miRNA, at least two miRNA or at least sixmiRNA, listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, if thelevel of expression of said of at least one miRNA, at least two miRNA orat least six miRNA, is higher than the control level of expression.

The method can comprise increasing the level of expression of said atleast one miRNA, at least two miRNA or at least six miRNA, which isunder-expressed with respect to the control level of expression. Themethod can comprise administering a therapeutically effective amount ofa composition comprising at least one miRNA, at least two miRNA or atleast six miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc,or a chemically synthesized miRNA mimetic or recombinant thereof. Themethod can comprise administering a therapeutically effective amount ofa composition comprising at least one miRNA, at least two miRNA or atleast six miRNA listed in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId,or a chemically synthesized miRNA mimetic or recombinant thereof. Themethod can comprise decreasing the level of expression of said at leastone miRNA, at least two miRNA or at least six miRNA, which isover-expressed with respect to the control level of expression. Themethod can comprise administering a therapeutically effective amount ofa composition comprising an inhibitor of at least one miRNA, at leasttwo miRNA or at least six miRNA listed in Tables Ia, Ic, IIa, IIc, Va,Vc, VIa, or VIc. The method can comprise administering a therapeuticallyeffective amount of a composition comprising an inhibitor of at leastone miRNA, at least two miRNA or at least six miRNA listed in Tables Ib,Id, IIb, IId, Vb, Vd, VIb or VId. The inhibitor can comprisedouble-filament RNA, short interfering RNA (siRNA), antisense nucleicacids, anti-miRNA oligonucleotides (AMOs), molecules of enzymatic RNA,or ribozymes.

The present invention also provides pharmaceutical compound comprisingat least one miRNA, at least two miRNA or at least six miRNA listed inTables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, chemically synthesizedmiRNA mimetic or recombinant thereof, or an inhibitor of the expressionof at least one miRNA, at least two miRNA or at least six miRNA listedin Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc and a pharmaceuticallyacceptable carrier.

The present invention also provides pharmaceutical compound comprisingat least one miRNA, at least two miRNA or at least six miRNA listed inTables Ib, Id, IIb, IId, Vb, Vd, VIb or VId, chemically synthesizedmiRNA mimetic or recombinant thereof, or an inhibitor of the expressionof at least one miRNA, at least two miRNA or at least six miRNA listedin Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId and a pharmaceuticallyacceptable carrier. Preferably, the miRNA are the miRNA listed in TablesIe, IIe, IIf, IIg, Ve, Vf, VIe or VIf.

The present invention provides a method for treating an individual inwhom the presence of a pulmonary tumour has been diagnosed or in whom arisk of developing a pulmonary tumour has been diagnosed, respectivelyfor the treatment of the pulmonary tumour or in order to reduce and/oreliminate the risk of developing a pulmonary tumour.

The method comprises the following steps of measuring an expressionlevel of at least one miRNA, at least two miRNA or at least six miRNAlisted in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, present in asample of biological fluid previously collected from an individual, andthen determining the miRNAs having values measured for the expressionlevel which deviate with respect to a predetermined and respectivecontrol criterion. The evaluation of the deviation with respect to acontrol criterion can use the procedures of the miRNA ratios describedabove for the various cases.

Once the overexpressed or underexpressed miRNAs have been determined,the method comprises altering the expression level of the miRNAs whoselevels of expression deviate with respect to the respective controlcriterion.

For example, in order to alter the expression level of the miRNAs theindividual can be administered with a pharmaceutical compound having aneffective quantity of at least one miRNA, at least two miRNA or at leastsix miRNA of the miRNAs listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa,or VIc if the expression level measured of the miRNA, or miRNAs, islower than a respective control expression level.

Alternatively, or in addition to the above, it is also possible toadminister the individual with a pharmaceutical compound having aneffective quantity of at least a compound for inhibiting the expressionof at least one miRNA, at least two miRNA or at least six miRNA listedin Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc if and for those miRNAswhose measured expression level is above the control expression level.

In this way the values of the expression level can be reset to thecontrol expression level for the underexpressed miRNAs with respect tothe respective control level of expression and/or it is possible toreduce the expression level for the overexpressed miRNAs.

With the aim of resetting the level of the underexpressed miRNAs atherapeutically effective quantity of a compound can be administeredwhich comprises at least one miRNA, at least two miRNA or at least sixmiRNA of the miRNAs of Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc,chemically synthesized (miRNA mimetics) or recombinant.

With the aim of reducing the expression level values to the controlexpression level for the overexpressed miRNAs with respect to therespective control expression level, a therapeutically effectivequantity of a compound can be administered which comprises at least onemiRNA, at least two miRNA or at least six miRNA inhibitor of a microRNAof Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc. The inhibitorcomprises, for example, one or more of the following: double-filamentRNA, optionally short interfering RNA (siRNA), antisense nucleic acids(anti-miRNA oligonucleotides (AMOs), molecules of enzymatic RNA(ribozymes). The inhibitor is directed to a specific product of microRNAand interferes with the expression (by inhibition of the translation orinduction of the degradation) of a target gene of the microRNA.

The administering of the above compounds (synthetic microRNAs or mimeticmiRNAs and inhibitors of microRNA) can for example can be done by meansof viral systems or nanoparticles containing microRNA or microRNAinhibitor) linked covalently with lipids or encapsulated liposomes.

The compounds can be administered by any means known in the art,including but not limited to, intranasal instillation, inhalation(aerosol), systemic administration (injection or infusion), directinoculation in the tumour (where present and visible), intrapleuricadministration, endopleuric administration or a combination thereof.

In terms of dosage, continuous and prolonged dosage can be performedover time. As miRNA molecules are “naturally” present in the organism,no relevant toxicity will obtain.

Biomarker Apparatuses and Kits

The present invention provides an article comprising a support having aplurality of sites, wherein each site is capable of receiving a quantityof a biological sample, wherein each of the sites comprises at least onereagent capable of binding with at least one miRNA, at least two miRNAor at least six miRNA, listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa,or VIc.

The reagent can be selected from group consisting of a polynucleotidecomprising a nucleotide sequence of at least one miRNA, at least twomiRNA, or at least six miRNA, from the miRNA listed in Tables Ia, Ic,IIa, IIc, Va, Vc, VIa, or VIc; a polynucleotide comprising a nucleotidesequence which is complementary to a sequence of at least one miRNA, atleast two miRNA, or at least six miRNA, from the miRNA listed in TablesIa, Ic, IIa, IIc, Va, Vc, VIa, or VIc; and a molecular probe configuredsuch as to recognize a sequence of at least one miRNA, at least twomiRNA, or at least six miRNA, from the miRNA listed in Tables Ia, Ic,IIa, IIc, Va, Vc, VIa, or VIc.

The present invention also provides an article comprising a supporthaving a plurality of sites, wherein each site is capable of receiving aquantity of a biological sample, wherein each of the sites comprises atleast one reagent capable of binding with at least one miRNA, at leasttwo miRNA or at least six miRNA, listed in Tables Ib, Id, IIb, IId, Vb,Vd, VIb, or VId. Preferably, the miRNA can be the miRNA listed in TableIe, IIe, IIf, IIg, Ve, Vf, VIe or VIf.

The present invention also provides an apparatus comprising at least oneunit capable of receiving at least one of the articles of the presentinvention; means for determining the level of expression of at least onemiRNA, at least two miRNA or at least six miRNA, listed in Tables Ia,Ic, IIa, IIc, Va, Vc, VIa, or VIc, and means for calculating the realquotients from among the levels of expression of at least one pair, atleast two pairs, or at least six pairs, of miRNA from the pairs of miRNAlisted in Tables IIIa, IIIc, IVa, IVc, VIIa, VIII, VIIIa, or VIIIc.

The means for determining the value of the level of expression can beselected from the group consisting of Quantitative Real-time PCR,Microfluidic cards, Microarrays, RT-PCR, quantitative orsemi-quantitative, Northern blot, Solution Hybridization, andSequencing.

The present invention provides medical kits useful for effectively andsimply applying the methods described above, for determining the risk ofcontracting a tumour or for tumour diagnosis, for example by using asample of blood removed from an individual.

In its general form the kit comprises a platform having a plurality ofsites, each of which is destined to receive a respective discretequantity of the sample of biological fluid (for example whole blood,serum, plasma, saliva or bronchial condensate). In the structural sensethe platform can be a support for a micro-fluidic card with the miRNA ofinterest with channellings for the distribution to the respective sitesof a predetermined number of samples of biological fluid. Each sitecomprises a reagent capable of bonding with at least one miRNA, at leasttwo miRNA or at least six miRNA of the microRNAs of Tables Ia, Ic, IIaor IIc for determining the risk of contracting a tumour or a reagentcapable of bonding with at least one miRNA, at least two miRNA or atleast six miRNA of the microRNAs of Tables Va, Vc, VIa or VIc for tumourdiagnosis, in such a way as to enable detectability with the apparatusdescribed herein below.

For example it can include at least one selected from a groupcomprising: a polynucleotide comprising a nucleotide sequence of atleast one miRNA, at least two miRNA or at least six miRNA of themicroRNAs as in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, apolynucleotide comprising a nucleotide sequence which is complementaryto a sequence of at least one miRNA, at least two miRNA or at least sixmiRNA of the microRNAs as in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, orVIc, a molecular probe configured such as to recognize a sequence of atleast one miRNA, at least two miRNA or at least six miRNA of themicroRNAs as in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.

The described medical kit can also be used with a medical apparatuscomprising a unit defining a seating for receiving one or more kits andmeans for determining the value of the expression of the microRNAs ofTables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc. Determining the value ofthe expression level can be performed by any means known in the art,including but not limited to, Quantitative Real-time PCR, Microfluidiccards, Microarrays, Quantitative or semi-quantitative RT-PCR, Northernblot, Solution Hybridization, Sequencing or combinations thereof.

The apparatus can also exhibit means for calculating the values of thereal ratios among values of expression levels of pairs of microRNAs asin Tables IIIa, IIIc, IVa, IVc, VIIa, VIII, VIIIa, or VIIIc. These meanscan comprise a programme and a processing unit in which the programmecontains instructions which when carried out by the processor enable acalculation of the ratios. Alternatively an analog circuit can beprovided which is able to perform the calculations.

miRNA

Overall, 24 miRNAs compose the signature of risk (R), signature ofaggressive disease (AR), signature of diagnosis (D) and signature ofpresence of aggressive disease (AD). Table IX recites those 24 miRNAsand how often they appear as part of a ratio for each signature.

TABLE IX miRNA R AR D AD hsa-miR-16 2 4 0 1 hsa-miR-17 4 4 3 3hsa-miR-21 0 5 0 1 hsa-miR-101 4 4 2 1 hsa-miR-126 1 1 2 4 hsa-miR-145 02 3 1 hsa-miR-197 5 9 6 13 hsa-miR-221 0 2 0 0 hsa-miR-320 1 2 3 0hsa-miR-451 7 10 0 11 hsa-miR-660 11 0 9 4 hsa-miR-106a 3 4 4 3hsa-miR-133a 3 0 0 0 hsa-miR-140-3p 2 1 0 0 hsa-miR-140-5p 0 0 2 2hsa-miR-142-3p 1 0 3 1 hsa-miR-148a 0 1 2 1 hsa-miR-15b 3 1 0 1hsa-miR-19b 3 1 2 4 hsa-miR-28-3p 1 8 4 4 hsa-miR-30b 0 2 0 1hsa-miR-30c 0 2 0 1 hsa-miR-486-5p 0 0 0 6 hsa-miR-92a 3 3 9 1

The present invention provides apparatuses and kits for detecting atleast one, at least two, at least three, at least four, at least six orall twenty-four of the miRNA of Table IX. The present invention providesapparatuses and kits for activating or stimulating the activity of orthe expression of at least one, at least two, at least three, at leastfour, at least six or all twenty-four of the miRNA of Table IX. Thepresent invention provides apparatuses and kits for decreasing orinhibiting the activity of or the expression of at least one, at leasttwo, at least three, at least four, at least six or all twenty-four ofthe miRNA of Table IX. The present invention also providespharmaceutical compositions for activating or stimulating the activityof or the expression of at least one, at least two, at least three, atleast four, at least six or all twenty-four of the miRNA of Table IX.The present invention also provides pharmaceutical compositions fordecreasing or inhibiting the activity of or the expression of at leastone, at least two, at least three, at least four, at least six or alltwenty-four of the miRNA of Table IX.

Table X provides a summary of the miRNA for use in all aspects of thepresent invention.

TABLE X miRNA Name Sequence hsa-miR-7-2CUGGAUACAGAGUGGACCGGCUGGCCCCAUCUGGAAGACUAGUGA (pre-miR)UUUUGUUGUUGUCUUACUGCGCUCAACAACAAAUCCCAGUCUACC UAAUGGUGCCAGCCAUCGCA(SEQ ID NO: 1) hsa-miR-7-2-5p UGGAAGACUAGUGAUUUUGUUGU (mature miR 5′arm) (SEQ ID NO: 2) hsa-miR-7-2-3p CAACAAAUCCCAGUCUACCUAA (mature miR 3′arm) (SEQ ID NO: 3) hsa-miR-15bUUGAGGCCUUAAAGUACUGUAGCAGCACAUCAUGGUUUACAUGCU (pre-miR)ACAGUCAAGAUGCGAAUCAUUAUUUGCUGCUCUAGAAAUUUAAGG AAAUUCAU (SEQ ID NO: 4)hsa-miR-15b-5p UAGCAGCACAUCAUGGUUUACA (mature miR 5′arm) (SEQ ID NO: 5)hsa-miR-15b-3p CGAAUCAUUAUUUGCUGCUCUA (mature miR 3′arm) (SEQ ID NO: 6)hsa-miR-16-1 GUCAGCAGUGCCUUAGCAGCACGUAAAUAUUGGCGUUAAGAUUCU(pre-miR from Chr.13) AAAAUUAUCUCCAGUAUUAACUGUGCUGCUGAAGUAAGGUUGAC(SEQ ID NO: 7) hsa-miR-16-2GUUCCACUCUAGCAGCACGUAAAUAUUGGCGUAGUGAAAUAUAUA (pre-miR from Chr.3)UUAAACACCAAUAUUACUGUGCUGCUUUAGUGUGAC (SEQ ID NO: 8) hsa-miR-16-5pUAGCAGCACGUAAAUAUUGGCG (mature miR 5′ arm) (SEQ ID NO: 9) hsa-miR-16-3pCCAAUAUUACUGUGCUGCUUUA (mature miR 3′arm) (SEQ ID NO: 10) hsa-miR-17GUCAGAAUAAUGUCAAAGUGCUUACAGUGCAGGUAGUGAUAUGUG (pre-miR)CAUCUACUGCAGUGAAGGCACUUGUAGCAUUAUGGUGAC (SEQ ID NO: 11) hsa-miR-17-5pCAAAGUGCUUACAGUGCAGGUAG (mature miR 5′arm) (SEQ ID NO: 12) hsa-miR-17-3pACUGCAGUGAAGGCACUUGUAG (mature miR 3′arm) (SEQ ID NO: 13) hsa-miR-19b-1CACUGUUCUAUGGUUAGUUUUGCAGGUUUGCAUCCAGCUGUGUGA (pre-miR from Chr. 13)UAUUCUGCUGUGCAAAUCCAUGCAAAACUGACUGUGGUAGUG (SEQ ID NO: 14)hsa-miR-19b-1-5p AGUUUUGCAGGUUUGCAUCCAGC (mature miR 5′arm from Chr. 13)(SEQ ID NO: 15) hsa-miR-19b-2ACAUUGCUACUUACAAUUAGUUUUGCAGGUUUGCAUUUCAGCGUA (pre-miR from Chr. X)UAUAUGUAUAUGUGGCUGUGCAAAUCCAUGCAAAACUGAUUGUGA UAAUGU (SEQ ID NO: 16)hsa-miR-19b-2-5p AGUUUUGCAGGUUUGCAUUUCA (mature miR 5′ arm from Chr. X)(SEQ ID NO: 17) hsa-miR-19b-3p UGUGCAAAUCCAUGCAAAACUGA (mature miR 3′arm from Chr. 13 (SEQ ID NO: 18) or X) hsa-miR-21UGUCGGGUAGCUUAUCAGACUGAUGUUGACUGUUGAAUCUCAUGG (pre-miR)CAACACCAGUCGAUGGGCUGUCUGACA (SEQ ID NO: 19) hsa-miR-21-5pUAGCUUAUCAGACUGAUGUUGA (mature miR 5′ arm) (SEQ ID NO: 20) hsa-miR-21-3pCAACACCAGUCGAUGGGCUGU (mature miR 3′ arm) (SEQ ID NO: 21) hsa-miR-28GGUCCUUGCCCUCAAGGAGCUCACAGUCUAUUGAGUUACCUUUCU (pre-miR)GACUUUCCCACUAGAUUGUGAGCUCCUGGAGGGCAGGCACU (SEQ ID NO: 22) hsa-miR-28-5pAAGGAGCUCACAGUCUAUUGAG (mature miR 5′ arm) (SEQ ID NO: 23) hsa-miR-28-3pCACUAGAUUGUGAGCUCCUGGA (mature miR 3′ arm) (SEQ ID NO: 24) hsa-miR-30aGCGACUGUAAACAUCCUCGACUGGAAGCUGUGAAGCCACAGAUGG (pre-miR)GCUUUCAGUCGGAUGUUUGCAGCUGC (SEQ ID NO: 25) hsa-miR-30a-5pUGUAAACAUCCUCGACUGGAAG (mature miR 5′ arm) (SEQ ID NO: 26)hsa-miR-30a-3p CUUUCAGUCGGAUGUUUGCAGC (mature miR 3′ arm)(SEQ ID NO: 27) hsa-miR-30bACCAAGUUUCAGUUCAUGUAAACAUCCUACACUCAGCUGUAAUAC (pre-miR)AUGGAUUGGCUGGGAGGUGGAUGUUUACUUCAGCUGACUUGGA (SEQ ID NO: 28)hsa-miR-30b-5p UGUAAACAUCCUACACUCAGCU (mature miR 5′ arm)(SEQ ID NO: 29) hsa-miR-30b-3p CUGGGAGGUGGAUGUUUACUUC (mature miR 3′arm) (SEQ ID NO: 30) hsa-miR-30c-1ACCAUGCUGUAGUGUGUGUAAACAUCCUACACUCUCAGCUGUGAG (pre-miR from Chr. 1)CUCAAGGUGGCUGGGAGAGGGUUGUUUACUCCUUCUGCCAUGGA (SEQ ID NO: 31)hsa-miR-30c-1-3p CUGGGAGAGGGUUGUUUACUCC (mature miR 3′ arm from Chr. 1)(SEQ ID NO: 32) hsa-miR-30c-2AGAUACUGUAAACAUCCUACACUCUCAGCUGUGGAAAGUAAGAAA (pre-miR from Chr. 6)GCUGGGAGAAGGCUGUUUACUCUUUCU (SEQ ID NO: 33) hsa-miR-30c-5pUGUAAACAUCCUACACUCUCAGC (mature miR 5′ arm from (SEQ ID NO: 34)Chr. 1 or 6) hsa-miR-30c-2-3p CUGGGAGAAGGCUGUUUACUCU (mature miR 3′arm from Chr. 6) (SEQ ID NO: 35) hsa-miR-30dGUUGUUGUAAACAUCCCCGACUGGAAGCUGUAAGACACAGCUAAG (pre-miR)CUUUCAGUCAGAUGUUUGCUGCUAC (SEQ ID NO: 36) hsa-miR-30d-5pUGUAAACAUCCCCGACUGGAAG (mature miR 5′ arm) (SEQ ID NO: 37)hsa-miR-30d-3p CUUUCAGUCAGAUGUUUGCUGC (mature miR 3′ arm)(SEQ ID NO: 38) hsa-miR-34bGUGCUCGGUUUGUAGGCAGUGUCAUUAGCUGAUUGUACUGUGGUG (pre-miR)GUUACAAUCACUAACUCCACUGCCAUCAAAACAAGGCAC (SEQ ID NO: 39) hsa-miR-34b-5pUAGGCAGUGUCAUUAGCUGAUUG (mature miR 5′ arm) (SEQ ID NO: 40)hsa-miR-34b-3p CAAUCACUAACUCCACUGCCAU (mature miR 3′ arm)(SEQ ID NO: 41) hsa-mirR-92a-1CUUUCUACACAGGUUGGGAUCGGUUGCAAUGCUGUGUUUCUGUAU (pre-miR from Chr. 13)GGUAUUGCACUUGUCCCGGCCUGUUGAGUUUGG (SEQ ID NO: 42) hsa-miR-92a-1-5pAGGUUGGGAUCGGUUGCAAUGCU (mature miR 5′ arm from Chr. 13) (SEQ ID NO: 43)hsa-miR-92a-3p UAUUGCACUUGUCCCGGCCUGU (mature miR 3′ arm from Chr. 13(SEQ ID NO: 44) or X) hsa-miR-92a-2UCAUCCCUGGGUGGGGAUUUGUUGCAUUACUUGUGUUCUAUAUAA (pre-miR from Chr. X)AGUAUUGCACUUGUCCCGGCCUGUGGAAGA (SEQ ID NO: 45) hsa-miR-92a-2-5pGGGUGGGGAUUUGUUGCAUUAC (mature miR 5′ arm from Chr. X) (SEQ ID NO: 46)hsa-miR-101-1 UGCCCUGGCUCAGUUAUCACAGUGCUGAUGCUGUCUAUUCUAAAG(pre-miR from Chr. 1) GUACAGUACUGUGAUAACUGAAGGAUGGCA (SEQ ID NO: 47)hsa-miR-101-5p CAGUUAUCACAGUGCUGAUGCU (mature miR 5′ arm from(SEQ ID NO: 48) Chr. 1 or 9) hsa-miR-101-1-3p UACAGUACUGUGAUAACUGAA(mature miR 3′ arm from Chr. 1) (SEQ ID NO: 49) hsa-miR-101-2ACUGUCCUUUUUCGGUUAUCAUGGUACCGAUGCUGUAUAUCUGAA (pre-miR from Chr. 9)AGGUACAGUACUGUGAUAACUGAAGAAUGGUGGU (SEQ ID NO: 50) hsa-miR-101-2-3pUACAGUACUGUGAUAACUGAA (mature miR 3′ arm from Chr. 9) (SEQ ID NO: 51)hsa-miR-106a CCUUGGCCAUGUAAAAGUGCUUACAGUGCAGGUAGCUUUUUGAGA (pre-miR)UCUACUGCAAUGUAAGCACUUCUUACAUUACCAUGG (SEQ ID NO: 52) hsa-miR-106a-5pAAAAGUGCUUACAGUGCAGGUAG (mature miR 5′ arm) (SEQ ID NO: 53)hsa-miR 106a-3p CUGCAAUGUAAGCACUUCUUAC (mature miR 3′ arm)(SEQ ID NO: 54) hsa-miR-126CGCUGGCGACGGGACAUUAUUACUUUUGGUACGCGCUGUGACACU (pre-miR)UCAAACUCGUACCGUGAGUAAUAAUGCGCCGUCCACGGCA (SEQ ID NO: 55) hsa-miR-126-5pCAUUAUUACUUUUGGUACGCG (mature miR 5′ arm) (SEQ ID NO: 56)hsa-miR-126-3p (mature miR 3′ UCGUACCGUGAGUAAUAAUGCG arm)(SEQ ID NO: 57) hsa-miR-133a-1ACAAUGCUUUGCUAGAGCUGGUAAAAUGGAACCAAAUCGCCUCUU (pre-miR from Chr. 18)CAAUGGAUUUGGUCCCCUUCAACCAGCUGUAGCUAUGCAUUGA (SEQ ID NO: 58)hsa-miR 133a-2 GGGAGCCAAAUGCUUUGCUAGAGCUGGUAAAAUGGAACCAAAUCG(pre-miR from Chr. 20) ACUGUCCAAUGGAUUUGGUCCCCUUCAACCAGCUGUAGCUGUGCAUUGAUGGCGCCG (SEQ ID NO: 59) hsa-miR-133a UUUGGUCCCCUUCAACCAGCUG(mature miR 3′ arm from (SEQ ID NO: 60) Chr. 18 or 20) hsa-miR-140UGUGUCUCUCUCUGUGUCCUGCCAGUGGUUUUACCCUAUGGUAGG (pre-miR)UUACGUCAUGCUGUUCUACCACAGGGUAGAACCACGGACAGGAUA CCGGGGCACC (SEQ ID NO: 61)hsa-miR-140-5p CAGUGGUUUUACCCUAUGGUAG (mature miR 5′ arm)(SEQ ID NO: 62) hsa-miR-140-3p UACCACAGGGUAGAACCACGG (mature miR 3′ arm)(SEQ ID NO: 63) hsa-miR-142GACAGUGCAGUCACCCAUAAAGUAGAAAGCACUACUAACAGCACU (pre-miR)GGAGGGUGUAGUGUUUCCUACUUUAUGGAUGAGUGUACUGUG (SEQ ID NO: 64)hsa-miR-142-5p CAUAAAGUAGAAAGCACUACU (mature miR 5′ arm) (SEQ ID NO: 65)hsa-miR-142-3p UGUAGUGUUUCCUACUUUAUGGA (mature miR 3′ arm)(SEQ ID NO: 66) hsa-miR-144UGGGGCCCUGGCUGGGAUAUCAUCAUAUACUGUAAGUUUGCGAUG (pre-miR)AGACACUACAGUAUAGAUGAUGUACUAGUCCGGGCACCCCC (SEQ ID NO: 67) hsa-miR-144-5pGGAUAUCAUCAUAUACUGUAAG (mature miR 5′ arm) (SEQ ID NO: 68)hsa-miR-144-3p UACAGUAUAGAUGAUGUACU (mature miR 3′ arm) (SEQ ID NO: 69)hsa-miR-145 CACCUUGUCCUCACGGUCCAGUUUUCCCAGGAAUCCCUUAGAUGC (pre-miR)UAAGAUGGGGAUUCCUGGAAAUACUGUUCUUGAGGUCAUGGUU (SEQ ID NO: 70)hsa-miR-145-5p GUCCAGUUUUCCCAGGAAUCCCU (mature miR 5′ arm)(SEQ ID NO: 71) hsa-miR-145-3p GGAUUCCUGGAAAUACUGUUCU (mature miR 3′arm)(SEQ ID NO: 72) hsa-miR-148aGAGGCAAAGUUCUGAGACACUCCGACUCUGAGUAUGAUAGAAGUC (pre-miR)AGUGCACUACAGAACUUUGUCUC (SEQ ID NO: 73) hsa-miR-148a-5pAAAGUUCUGAGACACUCCGACU (mature miR 5′ arm) (SEQ ID NO: 74)hsa-miR-148a-3p UCAGUGCACUACAGAACUUUGU (mature miR 3′ arm)(SEQ ID NO: 75) hsa-miR-197GGCUGUGCCGGGUAGAGAGGGCAGUGGGAGGUAAGAGCUCUUCAC (pre-miR)CCUUCACCACCUUCUCCACCCAGCAUGGCC (SEQ ID NO: 76) hsa-miR-197-5pCGGGUAGAGAGGGCAGUGGGAGG (mature miR 5′ arm) (SEQ ID NO: 77)hsa-miR-197-3p UUCACCACCUUCUCCACCCAGC (mature miR 3′ arm)(SEQ ID NO: 78) hsa-miR-200bCCAGCUCGGGCAGCCGUGGCCAUCUUACUGGGCAGCAUUGGAUGG (pre miR)AGUCAGGUCUCUAAUACUGCCUGGUAAUGAUGACGGCGGAGCCCU GCACG (SEQ ID NO: 79)hsa-miR-200b-5p CAUCUUACUGGGCAGCAUUGGA (mature miR 5′ arm)(SEQ ID NO: 80) hsa-miR-200b-3p UAAUACUGCCUGGUAAUGAUGA (mature miR 3′arm) (SEQ ID NO: 81) hsa-miR-205AAAGAUCCUCAGACAAUCCAUGUGCUUCUCUUGUCCUUCAUUCCA (pre-miR)CCGGAGUCUGUCUCAUACCCAACCAGAUUUCAGUGGAGUGAAGUU CAGGAGGCAUGGAGCUGACA(SEQ ID NO: 82) hsa-miR-205-5p UCCUUCAUUCCACCGGAGUCUG (mature miR 5′arm) (SEQ ID NO: 83) hsa-miR-205-3p GAUUUCAGUGGAGUGAAGUUC (mature miR 3′arm) (SEQ ID NO: 84) hsa-miR-210ACCCGGCAGUGCCUCCAGGCGCAGGGCAGCCCCUGCCCACCGCAC (pre-miR)ACUGCGCUGCCCCAGACCCACUGUGCGUGUGACAGCGGCUGAUCU GUGCCUGGGCAGCGCGACCC(SEQ ID NO: 85) hsa-miR-210 CUGUGCGUGUGACAGCGGCUGA (mature miR)(SEQ ID NO: 86) hsa-miR-219-1CCGCCCCGGGCCGCGGCUCCUGAUUGUCCAAACGCAAUUCUCGAG (pre-miR)UCUAUGGCUCCGGCCGAGAGUUGAGUCUGGACGUCCCGAGCCGCC GCCCCCAAACCUCGAGCGGG(SEQ ID NO: 87) hsa-miR-219-1-5p UGAUUGUCCAAACGCAAUUCU (mature miR 5′arm) (SEQ ID NO: 88) hsa-miR-219-1-3p AGAGUUGAGUCUGGACGUCCCG(mature miR 3′ arm) (SEQ ID NO: 89) hsa-miR-221UGAACAUCCAGGUCUGGGGCAUGAACCUGGCAUACAAUGUAGAUU (pre-miR)UCUGUGUUCGUUAGGCAACAGCUACAUUGUCUGCUGGGUUUCAGG CUACCUGGAAACAUGUUCUC(SEQ ID NO: 90) hsa-miR-221-5p ACCUGGCAUACAAUGUAGAUUU (mature miR 5′arm) (SEQ ID NO: 91) hsa-miR-221-3p AGCUACAUUGUCUGCUGGGUUUC(mature miR 3′ arm) (SEQ ID NO: 92) hsa-miR-320aGCUUCGCUCCCCUCCGCCUUCUCUUCCCGGUUCUUCCCGGAGUCG (pre-miR)GGAAAAGCUGGGUUGAGAGGGCGAAAAAGGAUGAGGU (SEQ ID NO: 93) hsa-miR-320aAAAAGCUGGGUUGAGAGGGCAA (mature miR) (SEQ ID NO: 94) hsa-miR-320b-1AAUUAAUCCCUCUCUUUCUAGUUCUUCCUAGAGUGAGGAAAAGCU(pre-miR from Chr. 1: 117214371- GGGUUGAGAGGGCAAACAAAUUAACUAAUUAAUU117214449) (SEQ ID NO: 95) hsa-miR-320b-2UGUUAUUUUUUGUCUUCUACCUAAGAAUUCUGUCUCUUAGGCUUU(pre-miR from Chr. 1: 224444706-CUCUUCCCAGAUUUCCCAAAGUUGGGAAAAGCUGGGUUGAGAGGG 224444843)CAAAAGGAAAAAAAAAGAAUUCUGUCUCUGACAUAAUUAGAUAGG GAA (SEQ ID NO: 96)hsa-miR-320b AAAAGCUGGGUUGAGAGGGCAA (mature miR from Chr. 1)(SEQ ID NO: 97) hsa-miR-320c-1UUUGCAUUAAAAAUGAGGCCUUCUCUUCCCAGUUCUUCCCAGAGU(pre-miR from Chr. 18: 19263471-CAGGAAAAGCUGGGUUGAGAGGGUAGAAAAAAAAUGAUGUAGG 19263558) (SEQ ID NO: 98)hsa-miR-320c-2 CUUCUCUUUCCAGUUCUUCCCAGAAUUGGGAAAAGCUGGGUUGAG(pre-miR from Chr. 18-21901650- AGGGU 21901699) (SEQ ID NO: 99)hsa-miR-320-c AAAAGCUGGGUUGAGAGGGU (mature miR from either Chr 18(SEQ ID NO: 100) loci) hsa-miR-320d-1UUCUCGUCCCAGUUCUUCCCAAAGUUGAGAAAAGCUGGGUUGAGA (pre-miR from Chr. 13) GGA(SEQ ID NO: 101) hsa-miR-320d-2UUCUCUUCCCAGUUCUUCUUGGAGUCAGGAAAAGCUGGGUUGAGA (pre-miR from Chr. X) GGA(SEQ ID NO: 102) hsa-miR-320d AAAAGCUGGGUUGAGAGGA(mature miR from Chr. 13 or X) (SEQ ID NO: 103) hsa-miR-320eGCCUUCUCUUCCCAGUUCUUCCUGGAGUCGGGGAAAAGCUGGGUU (pre-miR) GAGAAGGU(SEQ ID NO: 104) hsa-miR-320e AAAGCUGGGUUGAGAAGG (mature miR)(SEQ ID NO: 105) hsa-miR-324CUGACUAUGCCUCCCCGCAUCCCCUAGGGCAUUGGUGUAAAGCUG (pre-miR)GAGACCCACUGCCCCAGGUGCUGCUGGGGGUUGUAGUC (SEQ ID NO: 106) hsa-miR-324CGCAUCCCCUAGGGCAUUGGUGU (mature miR 5′ arm) (SEQ ID NO: 107) hsa-miR-324ACUGCCCCAGGUGCUGCUGG (mature miR 3′ arm) (SEQ ID NO: 108) hsa-miR-429CGCCGGCCGAUGGGCGUCUUACCAGACAUGGUUAGACCUGGCCCU (pre-miR)CUGUCUAAUACUGUCUGGUAAAACCGUCCAUCCGCUGC (SEQ ID NO: 109) hsa-miR-429UAAUACUGUCUGGUAAAACCGU (mature miR) (SEQ ID NO: 110) hsa-miR-451aCUUGGGAAUGGCAAGGAAACCGUUACCAUUACUGAGUUUAGUAAU (pre-miR)GGUAAUGGUUCUCUUGCUAUACCCAGA (SEQ ID NO: 111) hsa-miR-451aAAACCGUUACCAUUACUGAGUU (mature miR) (SEQ ID NO: 112) hsa-miR-451bUGGGUAUAGCAAGAGAACCAUUACCAUUACUAAACUCAGUAAUGG (pre-miR)UAACGGUUUCCUUGCCAUUCCCA (SEQ ID NO: 113) hsa-miR-451bUAGCAAGAGAACCAUUACCAUU (mature miR) (SEQ ID NO: 114) hsa-miR-486GCAUCCUGUACUGAGCUGCCCCGAGGCCCUUCAUGCUGCCCAGCU (pre-miRNA)CGGGGCAGCUCAGUACAGGAUAC (SEQ ID NO: 115) hsa-miR-486-5pUCCUGUACUGAGCUGCCCCGAG (mature miR 5′ arm) (SEQ ID NO: 116)hsa-miR-486-3p CGGGGCAGCUCAGUACAGGAU (mature miR 3′ arm)(SEQ ID NO: 117) hsa-miR-518eUCUCAGGCUGUGACCCUCUAGAGGGAAGCGCUUUCUGUUGGCUAA (pre-miR)AAGAAAAGAAAGCGCUUCCCUUCAGAGUGUUAACGCUUUGAGA (SEQ ID NO: 118)hsa-miR-518e 5p CUCUAGAGGGAAGCGCUUUCUG (mature miR 5′ arm)(SEQ ID NO: 119) hsa-miR-518e-3p AAAGCGCUUCCCUUCAGAGUG (mature miR 3′arm) (SEQ ID NO: 120) hsa-miR-660CUGCUCCUUCUCCCAUACCCAUUGCAUAUCGGAGUUGUGAAUUCU (pre-miR)CAAAACACCUCCUGUGUGCAUGGAUUACAGGAGGGUGAGCCUUGU CAUCGUG (SEQ ID NO: 121)hsa-miR-660-5p UACCCAUUGCAUAUCGGAGUUG (mature miR 5′ arm)(SEQ ID NO: 122) hsa-miR-660-3p ACCUCCUGUGUGCAUGGAUUA (mature miR 3′arm) (SEQ ID NO: 123)

Other features and advantages of the present invention are apparent fromthe different examples. The provided examples illustrate differentcomponents and methodology useful in practicing the present invention.The examples do not limit the claimed invention. Based on the presentdisclosure the skilled artisan can identify and employ other componentsand methodology useful for practicing the present invention.

EXAMPLES Example 1 Studies, Materials & Methods

The present invention investigated the expression profile of miRNA inthe plasma of individuals enrolled in screening protocols using spiralCT. This investigation was done with the aim of verifying the capabilityof miRNAs as a new class of biomolecular markers for: prediction of therisk of developing a tumour, in particular a pulmonary tumour, anddiagnosis of the tumour, in particular pulmonary tumour, and thus as aprognostic aid for discriminating patients with indolent or aggressivepulmonary lesions.

Plasma samples taken from smoker individuals were used, where theindividuals were over 50 years old, in a time parameter of between oneand two years before detection with CT spiral of the presence of apulmonary tumour in the same individuals. Also used were samples ofplasma collected at the moment of the appearance of the disease(detected using spiral CT). The plasma samples were obtained frompatients who had developed a pulmonary tumour with variouscharacteristics in terms of clinical aggressiveness (indolent nodules oradvanced and metastatic tumours) as well as from individuals whoremained free of disease for the whole duration of the screening.

In a first stage of the research, identification was made of themicroRNAs that were present in the plasma using microfluidic cards,model: TaqMan® of Applied Biosystems. Out of 378 microRNA analysed, 100were present stably in the plasma of healthy smoker individuals used asthe control group. Thus, with a large amount of starting data, there isa general agreement on the possibility of normalizing the expressionlevels of the single microRNAs on the mean of the expression levels ofthe 100 microRNAs for each individual (Mestdagh P et al. Genome Biol,2009). The data obtained using this type of normalization were comparedto those obtained by normalizing on potential microRNA housekeeping (forexample mir-16, mammU6, RNU44 or RNU48).

The inventors then thought of no longer using the values of theexpression levels of the single microRNAs, but instead the ratios amongpairs thereof. The value of the cycle threshold (Ct) obtained byqReal-Time PCR with the SDS 2.2.2® software (Applied Biosystems) wastransformed into the corresponding expression value (2^(−Ct)). Then theratio between the value of the expression level of each pair ofmicroRNAs possible was calculated, obtaining 4950 total ratios: the 4950total ratios were given by the formula 100*99/2 as the ratio between twomiRNAs and the reciprocal contain the same data. Finally the variationof these ratios (called “miRNA ratios”) in the plasma of the variousclasses of patients was analysed in order to identify plasma biomarkers.

The results showed that the microRNAs present in the greatest amount inthe ratios discriminating among the classes of patients are the same asthose which emerge from the analyses performed by normalizing on themean value of the expression levels of the 100 microRNAs for eachindividual, thus validating the method based on the miRNA ratios forquantifying the involved microRNAs.

In greater detail, with the aim of identifying biomarkers in the plasmawhich are able to predict the appearance of the pulmonary tumour, theinventors studied the expression profile of microRNAs circulating incollected samples up to two years preceding the diagnosis of the diseaseand at the moment of surgery in patients of two independent clinicaltrials, as mentioned above, for early diagnosis of pulmonary tumour inhigh-risk individuals (age >50 years and smokers) using spiral CT. Inthe first training set, made up of 40 samples of plasma from 19 patientsand 27 samples of plasma from healthy control individuals in 5 differentpools, the miRNA expression levels were analysed using TaqMan MicroRNAAssays (Applied Biosystems) with the aim of identifying thesignificantly-different miRNA ratios (p<0.05) between samples of plasmacollected pre-disease, at the moment of surgery and from healthyindividuals.

The specificity and sensitivity of the signatures of microRNAs thusobtained were compared with the validation set composed, as describedabove, of 32 plasma samples of 22 patients and 54 plasma samples ofhealthy control individuals, grouped in 10 different pools.

For the generalization of the signatures used for predicting theaggressiveness of the disease, the inventors grouped the two cohorts(training set and validation set) with the aim of obtaining a sufficientnumber for the statistical analysis. The cases with unfavorableprognosis were first compared to the respective controls and thesignatures thus obtained were tested to evaluate their effectivecapacity to discriminate the patients having poor prognosis from thosehaving good prognosis.

As already mentioned, the signatures of the microRNAs identified in thevarious analyses were validated on two independent sets constituted byhigh-risk individuals (smokers of more than 50 years of age) enrolled intwo different clinical trials for early identification of pulmonarytumour using low-dose spiral CT: a first set, or training set, made upof 40 samples of plasma from 19 patients and 27 samples of plasma fromhealthy control individuals grouped in 5 different pools and a secondset or validation set (i.e. in a second set of individuals) made up of32 samples of plasma from 22 patients and 54 samples of plasma fromhealthy control individuals, grouped in 10 different pools.

FIG. 1 summarizes the pathological clinical characteristics of thetraining set and the validation set selected for the analysis of theexpression levels of the miRNAs in the plasma samples.

To determine the microRNA profile in the plasma samples the total RNAwas extracted from 200 μl of plasma using the mirVana™ PARIS™ Kit(Ambion), eluting in 50 μl of elution buffer.

The expression levels were determined using q-Real Time PCR startingfrom 3 μl of elute first using the Megaplex™ Pools Protocol on amicrofluidic card, type A (Applied Biosystems), then the Multiplex™Pools Protocol (Applied Biosystems).

All the data was extrapolated using the Sequence Detection Systemsoftware (SDS 2.2.2® Applied Biosystems), setting the threshold manuallyat 0.2 and the baseline between 3 and 18 cycles (on a total of 40).

Apart from the standard equipment for molecular biology, use was made ofReal-time quantitative PCR 7900-HT (Applied Biosystems) and GeneAmp©9700 Sequence Detection System (Applied Biosystems).

Identification of a Signature Based on MiRNAs Able to IdentifyIndividuals at Risk of Developing Pulmonary Tumour

The samples of plasma collected 1-2 years before from patients in whom atumour was later diagnosed using spiral CT were analysed and comparedwith the control pool, constituted by healthy individuals.

A signature was therefore identified in the training comprising 14 miRNAratios made up of 14 microRNAs capable of correctly discriminating 18out of 20 pre-disease samples from individuals who then will develop thedisease (90% sensitivity), while only one control pool was positive forthis signature (80% specificity). In the validation set the sensitivitywas 80%, while the specificity was 90% (AUC-ROC=0.85, p<0.001).

The miRNA ratios of the first example were then listed and are reportedalso in FIG. 4A.

Q₁=hsa-mirR-106a/hsa-mirR-451

Q₂=hsa-mirR-140-5p/hsa-mirR-320

Q₃=hsa-mirR-140-5p/hsa-mirR-451

Q₄=hsa-mirR-140-5p/hsa-mirR-660

Q₅=hsa-mirR-140-5p/hsa-mirR-92a

Q₆=hsa-mirR-15b/hsa-mirR-92a

Q₇=hsa-mirR-17/hsa-mirR-451

Q₈=hsa-mirR-197/hsa-mirR-451

Q₉=hsa-mirR-19b/hsa-mirR-660

Q₁₀=hsa-mirR-221/hsa-mirR-660

Q₁₁=hsa-mirR-28-3p/hsa-mirR-660

Q₁₂=hsa-mirR-30b/hsa-mirR-92a

Q₁₃=hsa-mirR-30c/hsa-mirR-451

Q₁₄=hsa-mirR-30c/hsa-mirR-660

The predictive capacity of this signature was validated in samplescollected up to 28 months before the diagnosis of disease with spiral CTand the microRNAs most frequently deregulated were: mir-660, mir-140-5p,mir-451, mir-28-3p, mir-30c and mir-92.

Identification of the Signature Based on the MiRNAs Able to haveDiagnostic Value

Plasma samples collected at the moment of surgery or on identificationof the disease by spiral CT were compared with the control pools. In thetraining set, a panel of 16 miRNA ratios, made up of 13 microRNAs,correctly classify 16 out of 19 patients with a sensitivity of 84% and aspecificity of 80%. In the validation set sensitivity is 75% and thespecificity is 100% (AUC-ROC=0.88, p<0.0001).

A lower sensitivity in the validation set can be correlated to thepresence of a greater number of small indolent nodules, of which twopatients are part, whose blood samples were mis-matched both by the risksignature in the pre-disease samples, and by the signature in thesamples taken in the presence of disease.

The miRNA ratios of the second example are listed herein below and arealso reported in FIG. 4B.

Q₁=hsa-mirR-106a/hsa-mirR-140-3p

Q₂=hsa-mirR-106a/hsa-mirR-30c

Q₃=hsa-mirR-106a/hsa-mirR-486-5p

Q₄=hsa-mirR-140-3p/hsa-mirR-17

Q₅=hsa-mirR-140-5p/hsa-mirR-660

Q₆=hsa-mirR-15b/hsa-mirR-660

Q₇=hsa-mirR-15b/hsa-mirR-92a

Q₈=hsa-mirR-17/hsa-mirR-30c

Q₉=hsa-mirR-17/hsa-mirR-451

Q₁₀=hsa-mirR-17/hsa-mirR-486-5p

Q₁₁=hsa-mirR-19b/hsa-mirR-451

Q₁₂=hsa-mirR-19b/hsa-mirR-660

Q₁₃=hsa-mirR-19b/hsa-mirR-92a

Q₁₄=hsa-mirR-21/hsa-mirR-92a

Q₁₅=hsa-mirR-28-3p/hsa-mirR-660

Q₁₆=hsa-mirR-28-3p/hsa-mirR-92a

This diagnostic signature was then used to verify the presence ofdisease in the plasma samples collected before identification of thedisease by spiral CT. In the training set, 11 out of 20 (55%) of thecases are classified as being in presence of disease and, veryinterestingly, of these 11, 10 are either pessimistic diagnosis cases orbelonging to patients in whom the tumour was identified in the lateryears of the screening, or where more aggressive tumours with worseprognoses were identified.

Very similar results were obtained in the validation set, since in 10out of 15 (66.6%) pre-disease samples the signature of the presence ofdisease was presented. There are only 4 miRNA ratios in common betweenthe risk signatures and the diagnosis signatures; also partiallydifferent are the microRNAs involved: mir-17, mir-660, mir-92a,mir-106a, mir-19b are the most deregulated microRNAs at the moment ofthe diagnosis of pulmonary tumour.

Identification of a Signature Based on the MiRNAs for Risk ofDevelopment of Aggressive Pulmonary Tumour

The microRNA profiles of the pre-disease samples with unfavorableprognosis were identified and 10 miRNA ratios identified that were ableto recognize 5 out of 5 patients in the first set, 4 out of 5 in thevalidation set and with a specificity in both of 100%. Note thatmir-221, mir-660, mir-486-5p, mir-28-3p, mir-197, mir-106a, mir-451,mir-140-5p and mir-16 are the deregulated microRNAs.

The miRNA ratios of this third example are listed below and are alsoreported in FIG. 4C.

Q₁=hsa-mirR-106a/hsa-mirR-660

Q₂=hsa-mirR-140-5p/hsa-mirR-486-5p

Q₃=hsa-mirR-16/hsa-mirR-197

Q₄=hsa-mirR-197/hsa-mirR-486-5p

Q₅=hsa-mirR-197/hsa-mirR-660

Q₆=hsa-mirR-221/hsa-mirR-451

Q₇=hsa-mirR-221/hsa-mirR-660

Q₈=hsa-mirR-28-3p/hsa-mirR-451

Q₉=hsa-mirR-28-3p/hsa-mirR-486-5p

Q₁₀=hsa-mirR-28-3p/hsa-mirR-660

This signature was then tested on the pre-disease samples of thepatients having a good prognosis in the training set and in thevalidation set. The signature classifies, respectively in the two sets,33.3% and 45% of the samples; FIG. 2 illustrates a Kaplan-Meier survivalcurve of patients with or without the signature of risk of aggressivedisease; the curve with the aggressive signature is represented in acontinuous line and identified by RAD+ (risk of aggressive disease +)while the curve without the signature of risk of aggressive disease isrepresented by a discontinuous line and identified by RAD− (risk ofaggressive disease −) in plasma samples collected 1-2 years beforeidentification of the disease by spiral CT.

Of interest is the fact that the majority of the identified samplesbelong to individuals who developed the tumour between the III and the Vyear of screening, independently of the degree of the tumour. Thissupports the previous observation on the tumoral and normal samples oflung tissue, where a different profile of microRNA was presentrespectively in the tumoral and normal tissue of the same patients. Itis worthy of note that among the patients having a tumour diagnosed inthe second year of screening (all tumours at stage Ia and Ib), only onecase with stage Ib exhibited the signature of aggressive risk.

Identification of a Signature Based on MiRNAs for Prognosis of PatientsIdentified by Spiral CT

The samples from patients having a pessimistic prognosis, collected atthe moment of the diagnosis of the disease, were analysed, revealing asignature of 10 miRNA ratios, all containing mir-486-5p, whichidentifies 7 out of 8 patients with a pessimistic prognosis in thetraining set, 2 out of 3 of the validation set and no control pool ineither data set.

The miRNA ratios of this fourth example are listed below and are alsoreported in FIG. 4D.

Q₁=hsa-mirR-106a/hsa-mirR-486-5p

Q₂=hsa-mirR-126/hsa-mirR-486-5p

Q₃=hsa-mirR-142-3p/hsa-mirR-486-5p

Q₄=hsa-mirR-148a/hsa-mirR-486-5p

Q₅=hsa-mirR-15b/hsa-mirR-486-5p

Q₆=hsa-mirR-17/hsa-mirR-486-5p

Q₇=hsa-mirR-197/hsa-mirR-486-5p

Q₈=hsa-mirR-21/hsa-mirR-486-5p

Q₉=hsa-mirR-221/hsa-mirR-486-5p

Q₁₀=hsa-mirR-28-3p/hsa-mirR-486-5p

Further, only 2 out of 11 and 2 out of 13 patients having a goodprognosis, respectively in the first and second set, are positive forthis signature. FIG. 3 reports a Kaplan-Meier survival curve of patientswith or without the signatures for presence of aggressive disease(respectively identified with the continuous line of PAD+, which standsfor the presence of aggressive disease+, and with the broken line ofPAD−, standing for the presence of aggressive disease −) in plasmasamples collected at the moment of identification of the disease byspiral CT.

Further, this signature was used to classify the pre-disease samples inboth data sets. Half of the patients with pessimistic prognosis alsopresent this aggressiveness signature, while for those with goodprognosis of the 6 positives for this signature, 5 are tumoursidentified after the third year of screening.

Note that mir-486-5p, compared with mir-21, mir-126, mir-15b, mir-148a,mir-142-3p, mir-17, mir-197, mir-221, mir-28-3p and mir-106a, is alwaysunder-expressed in the plasma of patients with a pessimistic prognosis.

From the above-reported results, the inventors deduced that themicroRNAs present in the plasma are useful for identifying the presenceof the pulmonary tumour even 1-2 years before detection by spiral CT andfurther for predicting the development of types of more aggressivepulmonary cancer, indicating the possibility of selecting individuals athigh risk on the basis of profiles of circulating microRNA.

Example 2 miRNA Treatment

The instant example demonstrates modifying the level of two microRNAs ofour plasma signatures in a lung cancer cell line (A549). Mir-486 andmir-660 were down-modulated in plasma samples of patients with lungcancer and in particular in those who have developed the aggressive formof the disease. In FIG. 9 microRNA levels were measured by qReal-TimePCR in 20 paired tumor and normal lung tissue of the same patientsenrolled in the CT-screening trial used as validation set. Row Ct datawere normalized on the housekeeping miRNA RNU6B (DCt). The finalexpression values were obtained with the formula: 2̂(−DCt of the tumortissue)/2̂(−DCt of the normal lung). Values >1→upregulated in tumortissue. Values<1→downregulated in tumor tissue. The results in FIG. 9show that these two miRNA were downregulated in the tumor tissuecompared with the normal lung tissue.

In FIG. 10 mirVana™ miRNA Mimic (Applied biosystem) were used totransfect lung cancer cell line expressing constitutively the GreenFluorescence Protein (A549-GFP), accordingly with the Lipofectamine2000standard protocol (Invitrogen). 24 h hours after transfection, cellswere plated in multiwell plate to assess the proliferation capacity.Real time measurements of the GFP signal were measured every 24 h with afluorescent multiplate reader (Tecan M1000) using the wavelengths of theGFP. In FIG. 10, 549-GFP transfected with the miRNA mimic mir-486-5p andmir-660 showed a reduced proliferative capacity compared to the wildtype and the miRNA mimic scrambled (ctrl-) cell lines.

In FIG. 11, 549-GFP cells were transfected with miRNA mimics as reportedbefore. 24 h hour after transfection cell were plated in Falcon™FluoroBlok™ Cell Culture Inserts 8.0 μm (BD biosciences) placed in a24-wells plate. Cell migration capacity was assess measuring GFP signalusing the bottom reading tool of the Tecan M1000, in this way it waspossible to read just the signal of the cells passed through themembrane of the insert. Real time migration was followed for 4 days. InFIG. 11, 549-GFP transfected with the miRNA mimic mir-486-5p and mir-660showed a reduced migration capacity compared to the wild type and themiRNA mimic scrambled (ctrl-) cell lines.

Thus, the results show that if these two miRNA were restored in thecancer cell line the proliferation (FIG. 10) and the migration (FIG. 11)capability of cancer cells were significantly reduced. These preliminaryresults support the idea of using these miRNAs for a putativetherapeutic approach.

Example 3 Lung Cancer Detection and Survival

INT-IEO cohort (training set). Lung cancer was diagnosed in 38 subjects,22 in the first 2 y and 16 from the 3rd to 5th y of screening, includingone interval cancer at 4th y. The frequency of stage I was 63% (77% infirst 2 y vs. 44% in the last 3 y), and adenocarcinoma was 71% (95% infirst 2 y vs. 63% in the last 3 y; Table XI).

TABLE XI CT Year Characteristic 1-2 3-5 Total Lung Cancer 22 16 38Resected 21 (95) 12 (75) 33* (87)  Stage I 17 (77)  7 (44) 24 (63) StageII-IV  5 (23)  9 (56) 14 (37) Adeno 17 (95) 10 (63) 27 (71) *28 tumortissue and 24 normal lung samples were available for miRNA expressionanalysis. The number in parenthesis is the percent of all detected lungcancers.

Median follow-up time for the 38 lung cancer cases was 75 mo, with 60%5-y overall survival (95% C.I.: 43-74%). Five-y overall survival was 92%for stage 1 and 7% for stages II-IV (P<0.001; FIG. 12A). When the yearof detection was considered, 5-y overall survival was 77% for cancersdiagnosed in the first 2 y compared with 36% for those detected from 3rdto 5th y of screening (P=0.005; FIG. 12B), indicating that incidentcancers represent a more aggressive disease. Year of detection and tumorstage were significantly associated (χ² test, P=0.034). In the subset ofCT year 1-2/stage I, 5-y survival was 94% (95% C.I.: 65.0-99.1). In thewhole group of stage I, after exclusion of one death from second primarylung cancer and one from end-stage chronic obstructive pulmonarydisorder (COPD), 5-y survival was 100%.

Multicentric Italian Lung Detection (MILD) cohort (validation set). Atthe end of 4th year of screening in the MILD trial, lung cancer wasdiagnosed in 53 subjects, 24 in the first 2 y, and 23 in the 3rd and 4thyear. Six interval cancers were diagnosed: one in the 1st y, two in the2nd y, and three in the 3rd y. Early stage disease (Ia-Ib) was diagnosedin 28 (53%) patients, and adenocarcinoma was diagnosed in 30 (57%) ofpatients. Because this trial is ongoing, no interim analysis wasperformed so far. However, even if the median follow-up time of 23 mo isrelatively short, we could divide the 53 patients in two groups ofreasonable size: 14 patients with poor prognosis (dead or alive withincurable disease) and 39 patients with good prognosis (alive withoutdisease).

miRNA Expression Profiling in Tumor and Normal Lung

miRNA profiles of 28 tumors and 24 paired normal lung tissues wereanalyzed using a miRNA microarray platform. Validation of thedifferentially expressed miRNAs was done using qRT-PCR.

By class comparison and class prediction analyses (using both paired andunpaired algorithms), expression of 56 miRNAs was significantlydifferent at the nominal 0.001 level of the univariate test. The top 10deregulated miRNAs that discriminate CT-detected lung cancer from normallung tissue were: mir-7, mir-21, mir-200b, mir-210, mir-219-1, miR-324(up-regulated), mir-126, mir-451, mir-30a, and mir-486 (down-regulated;Table XII).

TABLE XII Tumor vs. miRNAs deregulated Normal Tissues (p < 0.001)Direction Fold Change mir-7-2-prec Up 1.3 mir-126 Down 0.4 mir-200b Up1.3 mir-210 Up 3.0 mir-219-1 Up 1.6 mir-21 Up 2.9 mir-324-5p Up 1.3mir-451 Down 0.5 mir-486-5p Down 0.5 mir-30a Down 0.6

This list included alterations previously identified in symptomatic lungcancer patients (e.g., mir-21 and the mir-200 family, known to beinvolved in pathways such as survival, apoptosis, epithelial-mesenchymaltransition) and some unidentified changes (e.g., down-regulation ofmiR-486 and miR-451).

To validate the results obtained with microarray hybridization, thelevels of the two most regulated miRNAs (mir-21 and mir-486) wereevaluated in tumor and normal samples by qRT-PCR, which confirmed theprevious observation.

mIRNA Expression in Tissues is Associated with Clinical-PathologicalFeatures

Possible association of miRNA expression profiles withclinical-pathological characteristics of the patients was theninvestigated (Table XIII). Two miRNAs (mir-205 and mir-21) significantlydiscriminated adenocarcinoma from squamous cell carcinoma histotypes(P≦0.001). Mir-518e and mir-144 were down-regulated in tumors with afaster growth rate, and higher levels of mir-429, member of the mir-200family, correlated with a worse disease-free survival (DFS).

TABLE XIII Clinical- Pathological Tumor Tissue Normal Tissue Charac-Direc- Direc- teristics miRNA tion P value miRNA tion P value Histotypemir-205 Down <0.001 (ADC v. SCC or others) mir-21- Up <0.001 pre GrowthRate mir-518e Up <0.001 mir- Up <0.001 Diameter 30d* (≧50% vs. >50%)mir-144- Up <0.001 pre Disease-free mir-429 Down 0.003 mir-34b Up 0.001Survival (Alive vs. Dead or Relapse)

The miRNA expression profile of tumors detected in the first 2 y of thescreening was significantly different from the profile of tumorsappearing after the 2nd y, with differential expression of eight miRNAs(mir-128, mir-129, mir-369-3p, mir-193, mir-339-3p, mir-185, mir-346,and mir-340). These results indicate that these groups of tumors displaydifferent miRNA profiles associated with distinct aggressive features,where the incident tumors grow faster.

miRNA expression analysis on normal lung tissues also discriminatedsubjects identified in the first 2 y from those of later years ofscreening (miR-126*, mir-126, let-7c, mir-222, mir-30e, mir-1-2,mir-29b-1, mir-30d-prec, mir-15a, mir-16; FIG. 13). Significantassociations were found between miRNAs expression in normal lung andreduction of forced expiratory volume (FEV; mir-379 and mir-29-1*),faster tumor growth (mir-30d*), DFS of the patients (mir-34b; TableXIII). The results obtained by microarray hybridization wereindependently validated by qRT-PCR.

Although there was no significant difference in smoking habits(packs-per-year, time from smoking cessation), patients detected inyears 3-5 showed a higher proportion of severe COPD (GOLD criteria≧2,33% vs. 5%; χ² test, P=0.02).

These findings indicate that specific miRNA signatures in normal lungmicroenvironment are associated with tumor aggressiveness and clinicalhistory of the patients.

Pathways Enrichment Analysis

For the miRNA signature discriminating tumor from normal samples,pathway enrichment analysis was performed using DIANA-mirPath softwareon the gene targets predicted by microT-4.0, Pic-Tar, and TargetScan-5.This analysis showed that many of the predicted miRNA targets areinvolved in critical pathway affected in cancer such as survival,apoptosis, epithelial-mesenchymal transition, and proliferation (XIV).

TABLE XIV KEGG Pathway (P < 0.001) No. of Genes MAPK Signaling Pathway159 Regulation of Actin Cytoskeleton 133 Focal Adhesion 130 WntSignaling Pathway 102 Axon Guidance 93 Insulin Signaling Pathway 92TGF-Beta Signaling Pathway 69 ErbB Signaling Pathway 64 AdherensJunction 62 Ribosome 3

mIRNA Expression Profiling in Plasma Samples: Study Design

Validated circulating biomarkers in plasma/serum could potentiallyrepresent the gold standard for a noninvasive routine clinicalapplication. We reasoned that ideal miRNA biomarkers should beidentified before the onset of the tumors and be able to predictaggressive versus indolent disease development.

To determine whether specific miRNA signatures are already detectable inplasma samples collected before the detection of the disease, weperformed high-throughput miRNA expression profiles of plasma samplesusing TaqMan microfluidic cards (Applied Biosystems). We first analyzedplasma samples collected >1 y before disease development and at the timeof disease detection (positive CT/surgery) in the training set(CT-screening trial INT-IEO). We generated miRNA signatures that werethen validated in plasma samples (also predisease and at diseasedetection) of a validation set (CT-screening MILD cohort). Theclinical-pathological characteristics of training and validation setsare shown in FIG. 1. As control groups, we tested 15 pools of plasmasamples (5-7 individuals per pool, 81 individuals in total) collectedfrom disease-free subjects (negative spiral-CT) from both trials, withage, sex, and smoking habits distribution similar to those of cases.

Using microfluidic cards, 113 miRNAs were found to be always expressedin all plasma samples, and a subset of 100 miRNAs was found to beconsistently expressed in the 15 control pools, with a goodreproducibility among biological duplicates (FIG. 15). These 100 miRNAswere then used to identify circulating biomarkers of risk, diagnosis,and prognosis in plasma samples collected before or in presence ofCT-detected disease.

miRNA Ratios as Bioinformatics Tools for miRNA Analysis

Because the normalization of miRNA data in plasma samples is still acontroversial issue, the ratios between the expression values of allmiRNAs consistently expressed in plasma were computed. Each value of asingle miRNA was compared with the values of all of the other 99 miRNAs,and 4,950 ratios were obtained and subsequently used to analyzedifferences between classes of samples resulting in the definition ofratios with clinical relevance. When using microfluidic cards, there isgeneral agreement on the normalization of single miRNA expression usingthe mean values of expression of all miRNAs of each card (13). Tovalidate the robustness of the miRNA ratios method, we compared theresults obtained independently by the two methods in the microfluidiccards. The results showed that the miRNAs mostly deregulated in multipleratios were the same as those detected using the normalization on themean expression value, thus confirming the robustness of the ratiosmethod.

The use of miRNA ratios seems to be an easily applicable method withpotential for general clinical use that avoids the need for large scale,high-throughput analyses and was therefore used to develop clinicallyuseful signatures based on circulating biomarkers.

Identification of Diagnostic and Prognostic Circulating miRNA Profilesin Plasma Samples Collected Before and at the Time of Disease Detection

Class comparison analysis was initially performed in the training set toidentify a group of miRNA ratios showing statistically significantdifferences between prediagnostic, diagnostic, and disease-free plasma(P<0.05). These ratios were then technically validated, in a subset ofsamples, by TaqMan MicroRNA assays.

To assess the consistency of miRNA ratios within the control pools, wecompared the value of each ratio in two control pools with the meanvalue resulting from the analysis of the individual samples composingthe pools. We found that the values were consistent.

However, because some ratios showed a high individual variability in thecontrol subjects, possibly leading to a high number of false positives,we considered for further analyses only those ratios with minimalintrapool variability.

The signatures obtained were then used to calculate specificity andsensitivity in an independent validation set.

Because the range of miRNA expression levels in the two datasets wasconsistently different, possibly due to a storage effect (14), thepatients in each dataset were compared with the respective controlgroups.

For the generation of the signatures predicting clinical outcome (bothbefore and in presence of CT-detected disease), because of the smallnumber of events, we grouped the two datasets. Cases with bad outcomewere compared with the respective control pools, and the signaturesobtained were then tested for their power to discriminate patients withbad (dead and alive with disease) or good (disease free) prognosis inthe whole cohort.

mIRNA Signature Identifies Individuals at Risk to Develop Lung Cancer

To investigate whether there are molecular markers predictingdevelopment of lung cancer, samples collected from patients 1 and/or 2 ybefore detection of the disease by CT were analyzed and compared withthe control pools of heavy-smoking individuals (FIG. 14A-14C).

A signature of 16 ratios composed by 15 miRNAs could discriminatecorrectly 18 of 20 samples from subjects developing lung cancer in thetraining set (90% sensitivity) and resulted positive in only 1 of the 5control pools (80% specificity). In the validation set, this signatureidentified 12 of 15 samples collected before lung cancer detection byspiral-CT, with sensitivity of 80% and specificity of 90% (AUC-ROC=0.85,P<0.0001; FIG. 4A). The predictive value of this signature was evaluatedto be useful up to 28 mo before the disease, and mir-660, mir-140-5p,mir-451, mir-28-3p, mir-30c, and mir-92a are the most frequentlyderegulated miRNAs.

mIRNA Signature with Diagnostic Value

Plasma samples collected at surgery or at time of disease detection byspiral CT were compared with pools of disease-free individuals toidentify a miRNA profile associated with lung cancer diagnosis. In thetraining set, a panel of 16 ratios involving 13 different miRNAsclassified 16 of 19 patients, with a sensitivity of 84% and aspecificity of 80%. In the validation set plasma samples, 12 of 16patients were correctly discriminated, with a sensitivity of 75% and aspecificity of 100% (AUC-ROC=0.88, P<0.0001; FIG. 4B).

The lower sensitivity observed may be related to the presence of ahigher number of small, early-stage nodules with indolent behavior inthis series and the inclusion of two patients misclassified by both thesignature of diagnosis and risk.

The diagnostic signature was then used for class prediction ofpredisease plasma samples in the same series. In the training set, 11 of20 (55%) cases were classified as individuals with disease and, veryinterestingly, 10 of these 11 cases were characterized by poor prognosis(dead or alive with disease) or belonged to the group of patientsidentified from 3rd to 5th y of screening. In the validation set,similar results were obtained, with presence of the disease signaturealready in 10 of 15 (66.6%) predisease plasma samples. Moreover, lookingat the three predisease samples of interval cancer cases (patients whodeveloped lung cancer few months after a negative CT result), only 1patient was classified by the risk signature. Instead, 2 cases(including the 1 identified by risk signature) already displayed thediagnostic signature 8-9 mo before disease detection. The intervalcancer case not recognized by any signatures had a stage 1a tumor withgood outcome, suggesting the presence of a low-risk nodule.

Only 4 ratios were shared by the signatures of risk and of diagnosis,and the miRNAs involved were partially different. mir-17, mir-660,mir-92a, mir-106a, and mir-19b were the most frequently deregulated atthe time of lung cancer diagnosis.

Overall, these findings strengthen the observation that circulatingmiRNA in plasma is detectable well before clinical disease detection byspiral CT, indicating the possibility to select high-risk groups on thebasis of miRNA profiling.

mIRNA Signature of Risk to Develop Aggressive Lung Cancer

We analyzed the miRNA expression profiles in predisease plasma samplesof individuals with poor clinical outcome to define a signature ofmiRNAs identifying individuals at high risk to develop an aggressivedisease.

A signature of 10 ratios, composed of 9 different miRNAs, identified 5of 5 patients with poor prognosis (dead or with progressive disease) inthis first set (100% sensitivity and 100% specificity). In thevalidation set, 4 of 5 patients with poor prognosis were correctlyclassified, including a patient with poor prognosis who developed aninterval cancer. The sensitivity of this signature in the validation setwas 80% with 100% specificity.

mir-221, mir-660, mir-486-5p, mir-28-3p, mir-197, mir-106a, mir-451,mir-140-5p, and mir-16 are the miRNAs deregulated in the signature ofaggressive disease.

The signature was then used for class prediction of predisease plasmasamples of patients with good prognosis in training and validation sets.The signature identified 5 of 15 (33.3%) patients in the training setand 5 of 11 (45%) patients in the validation set (FIG. 4C).Interestingly, in both the datasets, most of these classified samplesbelonged to patients whose tumor was detected after the 3rd y ofscreening. This finding supports our previous observation on tissuesamples where a distinct miRNA profile was identified in tumor andnormal tissues of the same patients. Noticeably, among the patients withtumor diagnosed in the 2nd y of screening (all stage 1a and 1b tumors),only one case with stage 1b tumor had the risk signature of aggressivedisease.

These results suggest that miRNA profiles in predisease plasma samplesare able to predict the development of tumors with worse prognosis andmight even be helpful in pinpointing those early stage tumors at highrisk of aggressive evolution.

mIRNA Expression in Plasma Samples at Time of Disease Detection andPrognosis

Then we looked at the association between miRNA expression and prognosisin plasma samples collected at the time of lung cancer diagnosis bygenerating a signature composed by 10 ratios, all containing mir-486-5p.This signature identified 7 of 8 patients with bad prognosis in thetraining set (88% sensitivity and 100% specificity). The signature ofaggressive disease was observed also in 2 of 10 samples with goodprognosis, one of these having a stage 1b tumor. In the validation set,only 3 plasma samples collected in presence of disease of patients withpoor prognosis were available, and 2 of these had the profile ofaggressive disease. The third case was misclassified by all of theanalyses performed in all plasma samples collected during screeningevaluations (FIG. 4D).

Again, this signature was used for class prediction of predisease plasmasamples of patients in the training and validation sets. Half of thepredisease samples of patients with bad prognosis were positive for boththe signatures of aggressive disease, whereas the predisease samples ofpatients with good prognosis that showed the signature of aggressivedisease belonged mainly (5 of 6) to patients with tumors detected afterthe 3rd y of screening. It is noteworthy that, although individuals inthe training set have an extended follow-up and 5-y overall survivaldata are available, the shorter median follow-up observation time (14mo) for patients in validation set might affect the strength of theprognostic signatures.

mir-486-5p, compared with mir-21, mir-126, mir-15b, mir-148a,mir-142-3p, mir-17, mir-197, mir-221, mir-28-3p, and mir-106a, appearsto be always down-regulated in plasma of patients with bad outcome.

Analysis

The investigation of biological and molecular features of indolent andaggressive lung cancer is critical to identify specific risk markers forlung cancer development, to achieve the earliest possible prediction andintervention and, potentially, to define novel therapeutic targets.

In this study, we have focused on the role of miRNAs as biomarkers oflung disease by taking advantage of the availability of both tissuesamples (tumor and normal lung) and multiple plasma samples, collectedbefore and at the time of disease detection, from patients enrolled intwo different spiral-CT screening trials with extended follow-up. Thesepatients developed tumors displaying variable aggressive behavior duringthe course of the trials.

Although previous studies reported miRNA expression profiles predictingrecurrence and prognosis only in lung tumor samples collected at thetime of surgery for symptomatic lung cancer, our study provides uniqueresults on miRNA signatures able to identify the presence of aggressivelung cancer not only in tumor, but also in normal lung tissues and inplasma samples of patients. Moreover, miRNAs deregulated in plasmasamples collected before clinical appearance of disease were powerfulmolecular predictors of high-risk disease development.

In tumor samples, we confirmed up-regulation of known miRNAs such asmir-21, a miRNA with proproliferative and anti-apoptotic function thatis reported to target PTEN, and described down-regulation of two miRNAs(mir-486 and mir-451) that are involved in maintenance of self-renewalcapacity of bronchio-alveolar stem cells. Association analyses revealedthat expression of mir-205 and mir-21 are markers linked to squamouscell carcinoma (SCC) and adenocarcinoma (ADC) histology, respectively,confirming previous studies on the validity of studying miRNA expressionin support of histopathological diagnosis for a precise classificationof tumor histology. Interestingly, miRNAs that were deregulated in themore aggressive tumors identified in later years of screening areinvolved in adhesion and invasion pathways: miR-339 was reported tonegatively regulate intercellular cell adhesion molecule (ICAM)-1, andmir-128a has been involved in TGFβ pathway promotion of tumor cellinvasion and metastasis. This miRNA specifically targets FOXO1A, atranscription factor involved in AKT signaling and apoptosis inhibition.

The finding of miRNA expression profiles associated with aggressivedisease and poor survival in normal lung tissues of the patientsstrengthens the existing evidence on the critical influence of thenormal lung microenvironment on tumor development and, in the presentstudy, on tumor aggressiveness. It is possible to speculate that thesemarkers might represent molecular signs of a “soil” that, afterextensive damage caused by smoking, becomes permissive, or evenpromoting, for cancer development. Several miRNAs deregulated in normallung tissue of the patients undergoing surgery are involved in majorpathways linked to cancer. In particular, miR-126 is known to promoteangiogenesis by repressing the inhibitors of VEGF signaling spred1 andpik3r2, and let-7 is involved in proinflammatory programs. In addition,AKT signaling is the major pathway influenced by miR-222, miR-30regulates connective tissue growth factor, and mir-29b modulatesanti-apoptotic and prometastatic matrix molecules by repressing Mc1-1.It is also interesting to note the down-regulation of mir-34b inpatients with worse DFS, because mir-34b is a well known target of p53,which cooperates to control cell proliferation and adhesion-independentgrowth. The observation of a possible prognostic role of several miRNAsin normal lung opens up the possibility of innovative therapeuticstrategies targeting the host rather than the tumor itself.

Because circulating miRNAs in plasma could be more tissue-specific thantumor-specific, we decided to perform a high-throughput miRNA expressionin plasma profiling using microfluidic cards. We then developedmultiplex real-time PCR assays to validate, as single PCR assays, thosemiRNA signatures significantly associated with clinical characteristicsof the patients. We have optimized simple and highly reproducible miRNAassays and formulated a suitable algorithm for qRT-PCR data validationin plasma using miRNA reciprocal ratios. Our findings suggest that theassessment of a number of miRNAs in plasma by qRT-PCR assays is apotentially useful and clinically applicable procedure to improve lungcancer management.

miRNAs deregulated in tissue specimens were rarely detected in plasmasamples, further strengthening the high tissue-specificity of miRNAs andsuggesting a predictive role of plasma miRNAs independent from tissuespecimens. We observed that a partially different set of miRNAs werederegulated in plasma before and at the time of disease. This findingmight be explained by the consideration that genes and pathwaysnecessary in the earlier phases of disease development are differentfrom those required for the maintenance and the progression of thetumor.

Overall, the 21 miRNAs composing the signatures of risk, diagnosis, andprognosis in plasma belong to major pathways: cellular aging (mir-19b,mir-17, mir-106), bronchioalveolar and hematopoietic stem cells renewal(mir-486, mir-106a, 142-3p), tumor recurrence in stage I NSCLC (mir-27b;mir-106a; mir-19b; mir-15b mir-16, mi-21), and lung canceraggressiveness (mir-221, mir-222). In particular mir-17, mir-92a,mir-19b, and mir-106a are oncomirs belonging to the same familyresponsible for increased proliferation, repression of apoptosis andinduction of angiogenesis. mir-197 regulates expression of the tumorsuppressor gene FUS1, whose expression is lost in a large proportion oflung tumors. mir-28-3p is located in a chromosomal region that isfrequently amplified in lung cancer (3q28). mir-221 blocks PTENexpression leading to activation of the AKT pathway, and is suggested toplay an important role in cell growth and invasiveness by targeting thePTEN/AKT pathway. Alterations of these pathways represent wellestablished and meaningful risk factors in lung cancer. Finally, in arecent publication regarding circulating miRNAs, mir-21, mir-126, andmir-486-5p were also identified as potential blood-based biomarkers withdiagnostic value in NSCLC patients.

The identification of miRNA signatures in plasma samples collected 1-2 ybefore disease that predict cancer development and prognosis ispotentially useful in the selection of high-risk individuals who need toundergo spiral-CT surveillance. It is noteworthy that specific miRNAsignatures in predisease plasma samples are able to predict anddiscriminate the development of the more aggressive, early metastatictumors that are frequently undetectable by yearly spiral-CT. Thisinformation could be certainly helpful to prompt these individuals inpharmacological smoking cessation programs and possibly to propose morespecific imaging for detection of occult metastatic disease (e.g., PET,whole-body MRI), as well as nontoxic treatments such as enrollment inprophylactic vaccination programs. Furthermore, the signature of apotentially aggressive disease could also help in the clinicalmanagement of the frequent early-stage nodules detected duringCT-screening trials improving diagnostic algorithms.

Considering the noninvasive characteristics of plasma sampling and thereproducible and easy detection of miRNA markers, plasma-based miRNAbiomarkers can be used in clinical practice and may help to avoidoverdiagnosis and overtreatment of low-risk disease and late detectionof high-risk and early metastatic disease (Boeri et al., Proc Natl AcadSci USA. 108(9):3713-8, 2011)

Materials and Methods

CT Screening Protocols. In the INT/IEO screening cohort of 1,035high-risk heavy smokers, the median age was 58 y (range 50-84), 739(71%) were men, average tobacco consumption was 26 cigarettes daily for37 y (median pack/years=40), and 14% were former smokers.

The following clinical parameters were evaluated: age, sex, pack/yearsindex, forced expiratory ventilation in 1 s (FEV1%), CT year,pathological stage of detected cancers, histology, size, growth rate,standard uptake value (SUV) of PET. The χ² test was used to examine theassociations between predictor variables. Overall survival (OS) curvesof lung cancer patients were estimated with the Kaplan-Meier method andcompared with the log-rank test, using time from lung cancer onset untildeath or by censoring at the last follow-up date. Statistical analyseswere carried out using SAS (SAS Institute Inc., Cary, N.C.) and Rsoftware. Two-sided P values <0.05 were considered statisticallysignificant.

The second trial was a prospective randomized trial named MulticentricItalian Lung Detection trial (MILD) launched in 2005 (MILD trial,validation set). Current or former smokers, at least 50 years old andwithout history of cancer within the prior 5 y, were randomized in twostudy groups: a control group undergoing a program of primary preventionwith pulmonary function test evaluation and an early-detection groupwhere periodic spiral-CT was associated with primary prevention andpulmonary function test evaluation. The early-detection group wasfurther randomized in two arms: yearly low-dose spiral CT vs. spiral CTevery 2 y. A total of 2,352 subjects were randomized in one of the twoCT screening arms.

During enrollment and annual recall of all volunteers in both trials,whole blood was collected in EDTA vacuum tubes and plasma immediatelyseparated by two centrifugation steps at 1,258 relative centrifugalforce×g at 4° C. and stored in a biological bank, supported by adatabase recording all clinical and epidemiological information. Tissuesamples from lung tumors and matching normal lung tissue (sampled atdistance from the cancer lesion) were also collected when available frompatients undergoing surgical resections. Tissue and plasma specimenswere obtained according to the Internal Review and the Ethics Boards ofthe Istituto Nazionale Tumori of Milan.

miRNA Microarray Analysis in Tissue Samples

For expression analyses, we first used a set of 28 snap-frozen spiral-CTdetected lung primary tumors and 24 paired normal lung tissues,collected during the INT/IEO trial. miRNA labeling and hybridization wasperformed using 5 μg of total TRIzol (Invitrogen) extracted RNA. ThemiRNA microarray (Ohio State University Comprehensive Cancer Center,version 2.0) used contained probes for 460 mature miRNAs spotted inquadruplicate (235 Homo sapiens, 222 Mus musculus, and three Arabidopsisthaliana) with annotated active sites selected for oligonucleotidedesign. Hybridization signals were detected with streptavidin-Alexa-647conjugate, and scanned images (Perkin-Elmer ScanArray XL5K Scanner) werequantified using the GeneSpring software version 7.2 (Silicon Genetics,Redwood City, Calif.).

Statistical and Bioinformatics Analyses on Tissue Samples

On the microarray chips, after background subtraction and datatransformation (to convert any negative value to 0.01), the averagevalue of the four spots was normalized using a per-chip 50th percentilemethod that normalizes each chip on its median.

Class Comparison and Class Prediction Analyses. Statistical analyseswere performed using BRB ArrayTools 3.8.1 software developed by Dr.Richard Simon at the National Cancer Institute. MicroRNA differentiallyexpressed between two classes were considered significant at the nominal0.001-0.003 level of the univariate test based on 10,000 randompermutations and were used for class prediction analyses with themultiple methods tool.

miRNA Profiling in Plasma Samples

miRNA expression profiling was performed in 40 plasma samples, collected12-28 mo before and at time of the disease detection, from 19 patientsin the training set and in 34 plasma samples from 22 patients from thevalidation set. Using mirVana PARISKit (Ambion), total RNA was extractedfrom 200-μl plasma samples, and miRNA expression was determined usingthe Megaplex Pools Protocol on microfluidic card type A (AppliedBiosystems). The control groups were represented by 15 pools of 5-7plasma samples each from disease-free individuals enrolled in the sametrials and matched to the patients by sex, age, and smoking habit. Foreach micro-fluidic card (sample), the Ct of every miRNA was determinedusing the program SDS 2.2.2 (Applied Biosystems) and setting a thresholdof 0.2 and a manual baseline from 3 to 18 cycles.

Quantitative Real-Time PCR. Tissues

Starting from 20 ng of total RNA in the reverse transcription (RT) step,TaqMan MicroRNA Assays (Applied Biosystems) were used for quantitativereal-time PCR following their standard procedures. Relativequantification was performed using the ΔΔCt method using as housekeepingthe miRNA RNU-6B.

Plasma samples. Starting from 3 n1 of the same plasma free-circulatingRNA used for the Megaplex Pools Protocol (Applied Biosystems), selectedmiRNAs were validated with the Multiplex Pools Protocol (AppliedBiosystems).

Results

FIG. 15 shows the consistency of miRNA expression measurement in plasmasamples by quantitative real-time PCR considering only the 100 miRNAsselected for class comparison analysis. (A) Technical duplicates wereperformed for two patient samples (341 and 380) and for a control pool(M2). The graphical representation was performed plotting the firstmiRNA values obtained on abscissa (duplicate A) and the values obtainedin the second evaluation in ordinate (duplicate B). The linearregression value shows a good reproducibility of measurements. (B)Correlation between two different control pools. (C) Graphicalrepresentation of average values of all Pearson correlation coefficientsbetween control pools, technical duplicates, and between all patientsamples (before and at time of disease).

1. A method comprising: determining the level of expression of at leasttwo miRNA from the miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa,or VIc in a biological sample from a subject, and comparing the level ofexpression of said miRNA from said sample from said subject to the levelof expression of said miRNA from a control biological sample.
 2. Themethod of claim 1, comprising determining the level of expression of atleast six miRNA from the miRNA listed in Tables Ia, Ic, IIa, IIc, Va,Vc, VIa, or VIc.
 3. A method comprising: determining the level ofexpression of at least two miRNA listed in Table Ib or Id in abiological sample from a subject, and comparing the level of expressionof said miRNA from said sample from said subject to the level ofexpression of said miRNA from a control biological sample, wherein achange or deviation in the level of expression of said at least twomiRNA in said biological sample from said control biological sampleidentifies a subject at risk of manifesting a tumor.
 4. The method ofclaim 3, comprising determining the level of expression of at least sixmiRNA listed in Table Ib or Id.
 5. The method of claim 3, wherein saidmiRNA are the miRNA listed in Table Ie.
 6. A method comprising:determining the level of expression of at least two miRNA listed inTable IIb or IId in a biological sample from a subject, and comparingthe level of expression of said miRNA from said sample from said subjectto the level of expression of said miRNA from a control biologicalsample, wherein a change or deviation in the level of expression of saidat least two miRNA in said biological sample from said controlbiological sample identifies a subject at risk of manifesting anaggressive tumor.
 7. The method of claim 6, comprising determining thelevel of expression of the six miRNA listed in Table IIb or IId.
 8. Themethod of claim 6, wherein said miRNA are the miRNA listed in Table IIe,IIf or IIg.
 9. A method comprising: determining the level of expressionof at least two miRNA listed in Table Vb or Vd in a biological samplefrom a subject, and comparing the level of expression of said miRNA fromsaid sample from said subject to the level of expression of said miRNAfrom a control biological sample, wherein a change or deviation in thelevel of expression of said at least two miRNA in said biological samplefrom said control biological sample determines the presence of a tumorin said subject.
 10. The method of claim 9, comprising determining thelevel of expression of the six miRNA listed in Table Vb or Vd.
 11. Themethod of claim 9, wherein said miRNA are the miRNA listed in Tables Veor Vf
 12. A method comprising: determining the level of expression of atleast two miRNA listed in Table VIb or VId in a biological sample from asubject, and comparing the level of expression of said miRNA from saidsample from said subject to the level of expression of said miRNA from acontrol biological sample, wherein a change or deviation in the level ofexpression of said at least two miRNA in said biological sample fromsaid control biological sample determines the presence of an aggressivetumor in said subject.
 13. The method of claim 12, comprisingdetermining the level of expression of the six miRNA listed in Table VIbor VId.
 14. The method of claim 12, wherein said miRNA are the miRNAlisted in Tables VIe or VIf.
 15. The method of claim 1, furthercomprising calculating a plurality of real quotients by determining aratio between the level of expression of at least one pair of miRNA fromat least two miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, orVIc; comparing each of the real quotients with a respective controlvalue; and determining the real quotients which deviate from therespective control quotient value.
 16. The method of claim 15,comprising determining a ratio between the level of expression of atleast one pair of miRNA from at least six miRNA listed in Tables Ia, Ic,IIa, IIc, Va, Vc, VIa, or VIc.
 17. The method of claim 15, wherein saidmiRNA are the miRNA listed in Tables Ie, IIe, IIf, IIg, Ve, Vf, VIe orVIf.
 18. The method of claim 15, further comprising determining a numberor percentage of real quotients which deviate from the respectivecontrol value.
 19. The method of claim 15, wherein for each of thecalculated quotients a respective control quotient is associated,represented by a ratio of the levels of expression for the miRNA in acontrol biological sample relative to a biological sample of a sametype.
 20. The method of claim 15, wherein calculating the plurality ofreal quotients comprises using the expression level of at least twomiRNA from the miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, orVIc.
 21. The method of claim 15, wherein calculating the plurality ofreal quotients comprises determining a predetermined number or apredetermined percentage of quotients from among the levels ofexpression, wherein the quotients are selected from at least one of thequotients as listed in Tables IIIa, IIIc, IVa, IVc, VIIa, VIIc, VIIIa,or VIIIc.
 22. The method of claim 21, wherein the quotients are selectedfrom at least six of the quotients as listed in Tables IIIa, IIIc, IVa,IVc, VIIa, VIIc, VIIIa, or VIIIc.
 23. An article comprising: a supporthaving a plurality of sites, wherein each site is capable of receiving aquantity of a biological sample, wherein each of the sites comprises atleast one reagent capable of binding with at least one miRNA listed inTables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
 24. The article of claim23, wherein each of the sites comprises at least one reagent capable ofbinding with at least two miRNA listed in Tables Ia, Ic, IIa, IIc, Va,Vc, VIa, or VIc.
 25. The article of claim 23, wherein each of the sitescomprises at least one reagent capable of binding with at least sixmiRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
 26. Thearticle of claim 23, wherein the reagent is selected from groupconsisting of: a polynucleotide comprising a nucleotide sequence of atleast one miRNA from the miRNA listed in Tables Ia, Ic, IIa, IIc, Va,Vc, VIa, or VIc; a polynucleotide comprising a nucleotide sequence whichis complementary to a sequence of at least one miRNA from the miRNAlisted in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc; and a molecularprobe configured such as to recognize a sequence of at least one miRNAfrom the miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.27. The article of claim 26, wherein comprising at least two miRNAlisted in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
 28. The articleof claim 26, wherein comprising at least six miRNA listed in Tables Ia,Ic, IIa, IIc, Va, Vc, VIa, or VIc.
 27. An article comprising: a supporthaving a plurality of sites, wherein each site is capable of receiving aquantity of a biological sample, wherein each of the sites comprises atleast one reagent capable of binding with at least two miRNA listed inTables Ib, Id, IIb, IId, Vb, Vd, VIb or VId.
 28. The article of claim27, wherein each of the sites comprises at least one reagent capable ofbinding with at least six miRNA listed in Tables Ib, Id, IIb, IId, Vb,Vd, VIb or VId.
 29. The article of claim 27, wherein said miRNA are themiRNA listed in Tables Ie, IIe, IIf, IIg, Ve, Vf, VIe or VIf.
 30. Anapparatus comprising: at least one unit capable of receiving at leastone of the articles of claim 23; means for determining the level ofexpression of at least one miRNA from the miRNA listed in Tables Ia, Ic,IIa, IIc, Va, Vc, VIa, or VIc, and means for calculating the realquotients from among the levels of expression of at least one pair ofmiRNA from the pairs of miRNA listed in Tables IIIa, IIIc, IVa, IVc,VIIa, VIIc, VIIIa, or VIIIc.
 31. The method of claim 3, furthercomprising altering the level of expression of at least one miRNA forwhich the level of expression changes or deviates, thereby reducing oreliminating the risk of developing a tumor in said subject.
 32. Themethod of claim 6, further comprising altering the level of expressionof at least one miRNA for which the level of expression changes ordeviates, thereby reducing or eliminating the risk of developing anaggressive tumor in said subject.
 33. The method of claim 9, furthercomprising altering the level of expression of at least one miRNA forwhich the level of expression changes or deviates, thereby treating atumor in said subject.
 34. The method of claim 12, further comprisingaltering the level of expression of at least one miRNA for which thelevel of expression changes or deviates, thereby treating an aggressivetumor in said subject.
 35. The method of claim 31, wherein altering thelevel of expression of said at least one miRNA comprises administeringto said subject a therapeutically effective amount of at least one miRNAlisted in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, or a chemicallysynthesized miRNA mimetic or recombinant thereof, if the level ofexpression of said at least one miRNA is lower than the control level ofexpression or administering to said subject a therapeutically effectiveamount of a compound capable of inhibiting the expression of at leastone miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, if thelevel of expression of said at least one miRNA is higher than thecontrol level of expression.
 36. The method of claim 35, comprisingadministering a therapeutically effective amount of a compositioncomprising at least one miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc,VIa, or VIc, or a chemically synthesized miRNA mimetic or recombinantthereof or administering a therapeutically effective amount of acomposition comprising an inhibitor of at least one miRNA listed inTables Ib, Id, IIb, Hd, Vb, Vd, VIb or VId.
 37. A pharmaceuticalcompound comprising: at least one miRNA listed in Tables Ia, Ic, IIa,IIc, Va, Vc, VIa, or VIc, chemically synthesized miRNA mimetic orrecombinant thereof, or an inhibitor of the expression of at least onemiRNA listed in Tables Ia, Ic, IIa, IIe, Va, Vc, VIa, or VIc and apharmaceutically acceptable carrier.
 38. The pharmaceutical compound ofclaim 37 comprising at least two miRNA listed in Tables Ia, Ic, IIa,IIc, Va, Vc, VIa, or VIc
 39. The pharmaceutical compound of claim 37comprising at least six miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc,VIa, or VIc
 40. A pharmaceutical compound comprising: at least one miRNAlisted in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId, chemicallysynthesized miRNA mimetic or recombinant thereof, or an inhibitor of theexpression of at least one miRNA listed in Tables Ib, Id, IIb, IId, Vb,Vd, VIb or VId and a pharmaceutically acceptable carrier.
 41. Thepharmaceutical compound of claim 40 comprising at least two miRNA listedin Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId
 42. The pharmaceuticalcompound of claim 40 comprising at least six miRNA listed in Tables Ib,Id, IIb, IId, Vb, Vd, VIb or VId
 43. The pharmaceutical compound ofclaim 40, wherein said miRNA are the miRNA listed in Tables Ie, IIe,IIf, IIg, Ve, Vf, VIe or VIf